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brainstorming:index [2019/03/29 17:06]
tdognon
brainstorming:index [2022/01/31 18:33] (current)
nbuisard
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-<​html><​div class="​pageTitle">​ Les partages de midi </​div></​html>​+<​html><​div class="​pageTitle">​ Les partages de midi </div><br></​html>​
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 +{{:​brainstorming:​img_20200922_1324191-panorama.jpg?​300|}} 
 +{{:​brainstorming:​capture_d_e_cran_2020-03-31_a_15.13.50_-_copie.png?​230|}}
 ====== Présentation ====== ====== Présentation ======
 ===== Qu'​est-ce que c'est ? ===== ===== Qu'​est-ce que c'est ? =====
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   * Tous les membres de l'​équipe sans exception sont invités à participer aux partages de midi.   * Tous les membres de l'​équipe sans exception sont invités à participer aux partages de midi.
   * Afin que nous soyons le plus nombreux possible aux partages de midi, merci d'​informer le/la coordinat-[eur/​rice] de vos absences.   * Afin que nous soyons le plus nombreux possible aux partages de midi, merci d'​informer le/la coordinat-[eur/​rice] de vos absences.
-  ​* Algorithme de détermination du prochain inscrit sur la liste des partages : si l'​inscription n'est pas spontanée alors elle n'est pas spontanée...+  ​
  
  
 ===== Coordination ===== ===== Coordination =====
-  * [[:members:maxime.peralta:​index| ​Maxime Peralta]]+  * [[:members:john.baxter:​index| ​John Baxter]] 
 +  * [[:​members:​noemie.buisard:​index| Noémie Buisard]]
  
 ====== Agenda ====== ====== Agenda ======
 +====== Vos rendez-vous ======
 +
 +
 +===== Mardi 14 Janvier 2021 13:00-14:00 =====
 +Présentation : Tiphaine Casy  \\  ​
 +**"​Enregistrement des données climatiques : Earth blackbox" ​ \\ ** 
 +"Basé sur le modèle des boîtes noires aériennes permettant de comprendre les causes d'un crash, des chercheurs et une compagnie de communication Australienne ont imaginé une "Earth black box" (ou "​Boîte noire de la Terre"​). Le rôle de cette dernière serait l'​enregistrement quotidiens des mouvements climatiques (fonte des glaces, augmentation du climat,...) des dépenses militaires, de la croissance démographique et des contenus de différents médias. Sa conception permettrait un stockage de 30 à 50 ans dans le but d'​informer les générations futures sur les actions ou non-actions orientant la Terre sur son déclin. Cette idée est venue suite à l'​observation de la progression continue du réchauffement climatique et de ses impacts écologiques,​ économiques et humains. Les chiffres actuels correspondent à ceux prédis en 1972 dans une étude menée par le MIT ("The limits of growth"​) et tendent vers un déclin total de la Terre vers la fin du siècle s'il n'y a aucune modification sociétale." ​ \\  ​
 +
 +
 +===== Mardi 21 Décembre 2021 13:00-14:00 =====
 +Présentation : Nicolas Vallée ​ \\  ​
 +**Présentation du projet CUFFSIM** ​
 +
 +===== Mardi 14 Décembre 2021 13:00-14:00 =====
 +Présentation : Enora Giffard ​ \\  ​
 +**Le stress post traumatique ​ \\ ** 
 +
 +===== Mardi 30 Novembre 2021 13:00-14:00 =====
 +Présentation : Tamás Haidegger ​ \\  ​
 +For the Noon sharing Tamás Haidegger, associate professor at Óbuda University, serving as the director of the University Research and Innovation Center (EKIK), and as the technical lead of medical robotics research at the Antal Bejczy Center for Intelligent Robotics.
 +His main field of research is on medical technologies,​ control/​teleoperation of surgical robots, image-guided therapy and digital health technologies. " ​ \\  ​
 +
 +
 +===== Mardi 23 Novembre 2021 13:00-14:00 =====
 +Présentation : Arnaud Huaulmé ​ \\  ​
 +"​Synapse is a platform for supporting scientific collaborations centered around shared biomedical data sets. Our goal is to make biomedical research more transparent,​ more reproducible,​ and more accessible to a broader audience of scientists. Synapse serves as the host site for a variety of scientific collaborations,​ individual research projects, and DREAM challenges." ​ \\  ​
 +
 +
 +===== Mardi 02 Novembre 2021 13:00-14:00 =====
 +Présentation : Alfonso Estudillo-Romero ​ \\  ​
 +"​Voxel-Based Diktiometry - Merging convolutional neural networks with voxel-based analysis for characterization of diffusion MRI for Parkinson’s disease." ​ \\  ​
 +
 +
 +===== Mardi 19 Octobre 2021 =====
 +Michaël Nguyen - Répétition de soutenance de stage  \\  14h : Delphine Tanguy - Répétition de soutenance de thèse
 +
 +===== Mardi 12 Octobre 2021 13:00-14:00 =====
 +Présentation : Alexandre Tronchot ​ \\  ​
 +**"​MENISIM,​ Simulation VR pour apprendre les bases de l'​arthroscopie : Retour sur les travaux de l'​année écoulée" ​ \\ ** 
 +
 +Voilà 1 an que le projet MENISIM a démarré (projet majeur de ma thèse de sciences). L'​objectif de ce Noon Sharing sera de vous faire un rappel sur l'​intérêt de ce travail dans la formation pratique à l'​arthroscopie des chirurgiens orthopédistes,​ une description de la méthodologie employée, et un retour sur les premiers résultats. Je conclurais cette présentation par les perspectives du projet, et une brève explication du projet de master 2 de Nicolas qu'il présentera de façon plus détaillée en fin d'​année.
 +
 +===== Mardi 05 Octobre 2021 13:00-14:00 =====
 +Présentation : Marie Le Duff  \\  ​
 +**"Les représentations sociales du changement climatique et des actions pro-environnementales du Plateau des Petites roches" ​ \\ ** 
 +
 +
 +===== Mardi 14 septembre 2021 13:00-14:00 =====
 +Présentation : Sonia Guérin ​ \\  ​
 +**Répétition de soutenance de Master : "​Outils d'​analyse d'une chirurgie : Hystérectomie robot-assitée" ​ \\ ** 
 +
 +
 +===== Mardi 07 septembre 2021 13:00-14:00 =====
 +Présentation : John Baxter ​ \\  ​
 +**Présentation de l'​expérience IHM (interaction homme-machine) sur un outil de segmentation du STN par l'​apprentissage automatique. ​ \\ ** 
 +
 +
 +===== Mardi 31 août 2021 13:00-14:00 =====
 +Répétition de soutenance de stage de fin d'​étude ​ \\  ​
 +Présentation : Enora Giffard
 +
 +
 +===== Mardi 15 Juin 2021 13:00-14:00 =====
 +
 +==== "​CARS2021 - Adapting the Listening Time for Micro-Electrode Recordings in Deep Brain Stimulation Interventions"​ ====
 +Présentation : Thibault Martin
 +
 +Abstract :
 +
 +" Deep Brain Stimulation (DBS) is a common treatment for a variety of neurological disorders which involves the precise placement of electrodes at particular subcortical locations such as the subthalamic nucleus. This placement is often guided by auditory analysis of micro-electrode recordings (MERs) which informs the clinical team as to the anatomic region in which the electrode is currently positioned. Recent automation attempts have lacked flexibility in terms of the amount of signal recorded, not allowing them to collect more signal when higher certainty is needed or less when the anatomy is unambiguous. Therefore, we have addressed this problem by evaluating a simple algorithm that allows for MER signal collection to terminate once the underlying model has sufficient confidence. We have parameterized this approach and explored its performance using three underlying models composed of one neural network and two Bayesian extensions of said network. Our results shown that one particular configuration,​ a Bayesian model of the underlying network'​s certainty, outperforms the others and is relatively insensitive to parameterization. Further investigation shows that this model also allows for signals to be classified earlier without increasing the error rate. This work presents a simple algorithm that records the confidence of an underlying neural network, thus allowing for MER data collection to be terminated early when sufficient confidence is reached. This has the potential to improve the efficiency of DBS electrode implantation by reducing the time required to identify anatomical structures using MERs. "
 +
 +===== Mardi 8 Juin 2021 13:00-14:00 =====
 +
 +==== " Robot-assisted laparoscopic hysterectomy:​ experts vs juniors " ====
 +Présentation : Sonia Guérin
 +
 +===== Mardi 1er Juin 2021 13:00-14:00 =====
 +
 +==== " Study of anatomical and clinical correlation in tractography after deep brain stimulation of the anterior nucleus of the thalamus (ANT) for focal, inoperable and drug resistant epilepsy. " ====
 +Présentation : Mathilde Gaudian
 +
 +===== Mardi 25 Mai 2021 13:00-14:00 =====
 +
 +==== " Présentation des résultats du stage " ====
 +Présentation : Tiphaine Casy
 +
 +===== Mardi 18 Mai 2021 13:00-14:00 =====
 +
 +==== " REPEAT - Simulation par Réalité Virtuelle : utilisation et apport dans l'​apprentissage de compétences non techniques dans la formation de l'​interne en neurochirurgie " ====
 +Présentation : Julien Tinois
 +
 +===== Mardi 11 Mai 2021 13:00-14:00 =====
 +
 +==== " Multimodal investigation of epileptic network, insight from electrophysiology and hemodynamic processes " ====
 +Présentation : Christophe Grova (PhD, Associate Professor, Physics Dpt, Concordia University ​ and  Adjunct Professor in Biomedical Engineering,​ and Neurology and Neurosurgery Dpt at McGill University)
 +
 +===== Mardi 20 avril 2021 13:00-14:00 =====
 +
 +==== "Le numérique responsable"​ ====
 +Présentation : Pierre Jannin
 +
 +===== Mardi 06 avril 2021 13:00-14:00 =====
 +
 +==== "​Bénéfice de l'​état de flow sur l'​efficacité des distractions dans la prise en charge de l’anxiété préopératoire en anesthésie pédiatrique"​ ====
 +Présentation : Camille Tordet
 +
 +"Les méthodes de distraction (jouet, dessin animé, jeu vidéo) ont été évaluées comme efficace dans la prise en charge de l’anxiété préopératoire des enfants. Les activités distractrices détournent l’attention des enfants des indices menaçants de la situation vers des activités et des pensées plus agréables. Toutefois, la variabilité d’efficacité de cette stratégie s’avère peu étudiée. En effet, si le bénéfice de la méthode de distraction s’explique par le transfert des ressources attentionnelles de la situation anxiogène vers l’activité distractrice,​ alors on devrait observer une variabilité d’efficacité selon le degré de ressources attentionnelles alloué sur l’activité. Ce travail cherche à analyser comment l’état de flow (état de concentration et d'​absorption intense) peut fournir des explications,​ dans le but d’améliorer les distractions actuellement utilisées. ​
 +Cette présentation abordera le contexte puis l’étude que nous avons menée au CHU de Rennes Sud, afin d’apporter des éléments de réponse à ces questions."​
 +
 +
 +===== Mardi 30 Mars 2021 13:00-14:00 =====
 +
 +==== "Brain correlates of behavioural disinhibition in behavioural variant frontotemporal dementia."​ ====
 +Présentation : Delphine Tanguy
 +
 +"​Disinhibition is a core symptom in neurodegenerative diseases, in particular in fronto-temporal dementia (FTD), and a major cause of stress for caregivers. However, the concept of this symptom is hard to disentangle:​ while a distinction between behavioural and cognitive disinhibition is common, an operational definition of behavioural disinhibition remains unclear. Therefore, available assessments of these behavioural disorders are imprecise and the corresponding neuroanatomical correlates are non-univocal.Thus,​ we aimed to characterise the anatomical networks underlying different subtypes of behavioural disinhibition. For this purpose, we used an original semi-ecological task assessing two specific dimensions of behavioural disinhibition,​ such as compulsivity and social disinhibition,​ in 17 behavioural variant of FTD patients and 18 healthy controls, associated with classic neuropsychological tests and brain imaging (voxel-based morphometry for the grey matter, tractography for the white matter). Compulsivity correlated with right temporal regions atrophy and with alterations of the bilateral cingulum and uncinate fasciculus, the right inferior longitudinal fasciculus and the right arcuate fasciculus. Social disinhibition was associated to huge bilateral frontal atrophy and impairments in the cingulum, the forceps minor and the left uncinate fasciculus. By combining ecological behavioural analyses with neuroanatomy,​ we identified two subtypes of behavioural disinhibition associated with differential neural networks."​
 +
 +===== Mardi 23 Février 2021 13:00-14:00 =====
 +
 +==== " Automatic Cortical Target Point Localisation in MRI for Transcranial Magnetic Stimulation via a Multi-Resolution Convolutional Neural Network " ====
 +Présentation : John S H Baxter
 +
 +" Transcranial Magnetic Stimulation (TMS) is a growing therapy for a variety of psychiatric and neurological disorders that arise from or are modulated by cortical regions of the brain represented by singular 3D target points. These target points are often determined manually with assistance from a pre-operative T1-weighted MRI, although there is growing interest in automatic target point localisation using an atlas. However, both approaches can be time-consuming which has an effect on the clinical workflow and the latter does not take into account patient variability such as the varying number of cortical gyri where these targets are located. This paper proposes a multi-resolution convolutional neural network for point localisation in MR images for a priori defined points in increasingly finely resolved versions of the input image. This approach is both fast and highly memory efficient, allowing it to run in high-throughput centres, and has the capability of distinguishing between patients with high levels of anatomical variability. Preliminary experiments have found the accuracy of this network to be 7.26+5.30 mm, compared to 9.39+4.63 mm for deformable registration and 6.94+5.10 mm for a human expert. The human-level performance of this network indicates that it can improve TMS planning by automatically localising target points in seconds, avoiding more time-consuming registration or manual point localisation processes. " ​
 +
 +===== Mardi 16 Février 2021 13:00-14:00 =====
 +
 +==== " PETRAW: PEg TRAnsfer Workflow recognition by different modalities " ====
 +Présentation : Arnaud Huaulmé
 +
 +" Automatic and online recognition of surgical workflows is mandatory to bring computer-assisted surgery (CAS) applications inside the operating room. According to the type of surgery, different modalities could be used for workflow recognition. In the case of robotic-assisted surgeries and virtual reality training sessions, video and kinematic data are easily available. However, even if these modalities are available, numerous methods on state of art only focus on one of them. Last year we submitted the MISAW sub-challenge as part of EndoVis at MICCAI2020 (challenge description and results available at https://​www.synapse.org/​MISAW,​ paper under writing), offering to participant to combine both modalities for the workflow recognition. To the best of our knowledge, there are very few studies about the added value to combine multiple modalities. Whereas, some study as demonstrate that the addition of external information improve the recognition,​ as the presence of tools
 +
 +PETRAW is a sub-challenge of ENDOVIS 2021 currently on minor revision for MICCAI2021. PETRAW focuses on the comparison of 3 modalities (video, kinematic, and segmentation) and their combination on surgical workflow recognition. On this noon sharing, I will present the challenge design and probably partial results." ​
 +
 +===== Mardi 9 Février 2021 13:00-14:00 =====
 +
 +==== " Preliminary results on the characterization of PD from DT images on the PPMI dataset by means of CNNs" ====
 +Présentation : Alfonso Estudillo Romero
 +
 +" We present our preliminary results on the analysis of diffusion tensor images (DTI) by means of a Convolutional Neural Network (CNN) to classify Parkinsonian patients (PD) and healthy controls (HC) from brain images. ​ An analysis of the whole population registered in a common space is proposed to compute some of the classical anisotropy measures in a voxel-based approach. Moreover, we retrieved the back-propagated gradients of these images through the CNN to understand how sensitive the CNN is to some anisotropy measures at some particular regions. " ​
 +
 +===== Mardi 2 Février 2021 13:00-14:00 =====
 +
 +==== " Extending Deep Neural Networks with Bayesian Inference and Recurrent Layers for Localizing the Subthalamic Nucleus from Micro-Electrode Recordings"​ ====
 +Présentation : Thibault Martin
 +
 +" Deep brain stimulation (DBS) is an interventional treatment for Parkinson'​s disease which involves the precise positioning of stimulation electrodes within particular subcortical anatomy. Although originally identified via imaging, additional inter-operative guidance is necessary to localize the target anatomy. Analysis of Micro-Electrode Recordings (MERs) allows for a trained neurophysiologist to infer the underlying anatomy at a particular electrode position using human audition, although it is subjective and requires a high degree of expertise. This project aims to develop and validate a deep neural network to assist in MER analysis during DBS which can use arbitrary length MERs while providing feedback to the neurophysiologist as to the model'​s certainty. We evaluate six different deep learning based classifiers which can use arbitrary length MERs for Sub-Thalamic Nucleus (STN) segmentation,​ finding a particular Baysian network to perform the best. With a view to providing decision support, the use of Bayesian inference has also made it possible to interpret the level of confidence in the predictions underlying the predictive model. This work represents a step forward in integrating automated analysis of MERs into the DBS surgical workflow by automatically finding and exploiting MER in a data-driven predictive model. " ​
 +
 +===== Mardi 5 Janvier 2021 13:00-14:00 =====
 +
 +==== " Place de l’Apprentissage de la Chirurgie Arthroscopique utilisant la Simulation en Réalité Virtuelle (VR) à propos d’un Geste : la Méniscectomie - MENISIM-VR"​ ====
 +Présentation : Alexandre Tronchot
 +
 +"Les dernières années ont été marquées par d'​importantes avancées dans la formation initiale des jeunes chirurgiens avec du temps alloué supplémentaire et de nouveaux outils pédagogiques. Toutefois, le quotidien reste essentiellement occupé par le temps de service. Paradoxalement,​ les internes vont être mis en responsabilité plus vite avec un temps passé à l'​hôpital plus court. La formation initiale doit donc à la fois assurer sa mutation et rester efficiente en trouvant des compléments et alternatives au traditionnel compagnonnage. La simulation est l'un des outils proposés pour cela, et elle a déjà fait ses preuves dans le domaine comportemental. Son évolution vers la réalité virtuelle (VR) est maintenant proposée pour la formation procédurale car elle offre un outil à la frontière entre réalités théorique et pratique et, surtout, inlassablement reproductible. La chirurgie arthroscopique est particulièrement adaptée à cette simulation VR du fait de son retour visuel per-opératoire sur écran 2D. Toutefois, et bien qu'il y ait de plus en plus d'​articles scientifiques parlant de l'​intérêt de la simulation VR en chirurgie arthroscopique,​ peu rapportent sa validité lors de la transposition des performances du simulateur vers le patient réel. Montrer que l'​étudiant en progressant sur simulateur devient également performant au bloc opératoire serait une avancée considérable dans la formation médicale du troisième cycle, correspondant parfaitement aux demandes des Ministères de la Santé et de l'​Enseignement Supérieur et la Recherche à la fois en termes de sécurité patient ("​Jamais la première fois sur le patient"​),​ mais aussi de sécurité du praticien et d'​enjeux économiques de formation." ​
 +
 +===== Mardi 8 Décembre 2020 13:00-14:00 =====
 +
 +==== "​Hystérectomie : indications,​ modalités et apports de la chirurgie robot assistée."​ ====
 +Présentation : Sonia Guerin
 +
 +"​Hysterectomy is the most commonly performed gynecological procedure in high income countries. Eight-seven percent of indications are benign diseases. Several surgical approaches are possible, each with its own advantages and disadvantages. With the arrival of the surgical robot, it is now possible for us to study precisely the gestures performed by the surgeon thanks to kinematics and video data analysis.
 +Initially, we will look at the indications,​ approaches and complications of hysterectomy before discussing the contribution of kinematic and video data in general surgery and in hysterectomy in particular." ​
 +
 +===== Mardi 1er Décembre 2020 13:00-14:00 =====
 +
 +==== "A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging"​ ====
 +Présentation : Bernard Gibaud
 +
 +"​Medical ionizing radiation procedures and especially medical imaging are a non negligible source of exposure to patients. Whereas the biological effects of high absorbed doses are relatively well known, the effects of low absorbed doses are still debated. This work presents the development of a computer platform called Image and Radiation Dose BioBank (IRDBB) to manage research data produced in the context of the MEDIRAD project, a European project focusing on research on low doses in the context of medical procedures. More precisely, the paper describes a semantic database linking dosimetric data (such as absorbed doses to organs) to the images corresponding to X-rays exposure (such as CT images) or scintigraphic images (such as SPECT or PET images) that allow measuring the distribution of a radiopharmaceutical.
 +
 +The main contributions of this work are: 1) the implementation of the semantic database of the IRDBB system and 2) an ontology called OntoMEDIRAD covering the domain of discourse involved in MEDIRAD research data, especially many concepts from the DICOM standard modelled according to a realist approach."​
 +
 +
 +===== Mardi 10 Novembre 2020 13:00-14:00 =====
 +
 +==== "​Flexible recurrent neural network for Audio-Visual sequence analysis"​ ====
 +Présenté par : Tsiry Mayet
 +
 +"Deep learning models are now brought closer to the user rather than running in a distant cloud, helping to reduce latency, network congestion, and improving data security and privacy. However, smartphones and user devices impose additional constraints such as limited computation or energy. Handling these constraints has become an active research topic. User devices can also host multiple processes running at the same time and starting or stopping abruptly, modifying the constraints affecting the processes. Few works have considered models that can be modified at run time to adapt to an evolving computational limit." ​
 +
 +===== Mardi 20 Octobre 2020 13:00-14:00 =====
 +
 +==== "Data driven methods to support decision making in Deep Brain Stimulation for Parkinson’s Disease " ====
 +Présenté par : Maxime Peralta (Répétition de soutenance de thèse)
 +
 +===== Mardi 13 Octobre 2020 13:00-14:00 =====
 +
 +==== "MISAW - Part of the Endoscopic Vision Challenge"​ ====
 +Présenté par : Arnaud Huaulmé
 +
 +"​Automatic and online recognition of surgical workflows is mandatory to bring computer-assisted surgery (CAS) applications inside the operating room. According to the type of surgery, different modalities could be used for workflow recognition. In the case where the addition of multiple sensors is not possible, the information available for manual surgery is generally restricted to video-only. In the case of robotic-assisted surgery, kinematic information is also available. It is expected that multimodal data would make easier automatic recognition methods.
 +
 +The “MIcro-Surgical Anastomose Workflow recognition” (MISAW) sub-challenge provides a unique dataset for online automatic recognition of surgical workflow by using both kinematic and stereoscopic video information on a micro-anastomosis training task. Participants are challenged to recognize online surgical workflow at different granularity levels (phases, steps, and activities) by taking advantage of both modalities available. Participants can submit results for the recognition of one or several granularity levels. In the case of several granularities,​ participants are encouraged (but not required) to submit the result of a multi-granularity workflow recognition,​ i.e. recognize different granularity levels thanks to a unique model."​
 +
 +===== Mardi 22 Septembre 2020 13:00-14:00 =====
 +
 +==== "​Characterisation of three clinical-neurological subtypes of the bvFTD based on inhibition deficit symptoms assessed through an ecological approach"​ ====
 +Présenté par : Delphine Tanguy
 +
 +===== Mardi 15 Septembre 2020 13:00-14:00 =====
 +
 +==== "​Review of my work" ====
 +Présenté par : Kevin Le Mut
 +
 +"​During 1 year of contract I carried out various works at MEDICIS. My main objective was the annotation of hysterectomy videos but I also participated in the annotations of the MISAW project and started to develop an application. In addition to this, various tasks were added to complete my work such as annotation protocol build on SurgePlan. The year 2020 was full of hazards that slowed down the progress of the work."
 +
 +===== Mercredi 09 Septembre 2020 16:00-17:00 =====
 +
 +==== "​Shared meeting with the VASST team" ====
 +Présenté par : Thibaut Dognon
 +
 +===== Mercredi 08 Juillet 2020 16:00-17:00 =====
 +
 +==== "​Shared meeting with the VASST team" ====
 +Présenté par : Maxime Peralta
 +
 +===== Mardi 30 Juin 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Advancing Our Understandings of Healthcare Team Dynamics From the Simulation Room to the Operating Room: A Neurodynamic Perspective"​ ====
 +Présenté par : Thibaut Dognon
 +
 +"The initial models of team and team member dynamics using biometric data in healthcare will likely come from simulations. But how confident are we that the simulation-derived high-resolution dynamics will reflect those of teams working with live patients? We have developed neurodynamic models of a neurosurgery team while they performed a peroneal nerve decompression surgery on a patient to approach this question. The models were constructed from EEG-derived measures that provided second-by-second estimates of the neurodynamic responses of the team and team members to task uncertainty. The anesthesiologist and two neurosurgeons developed peaks, often coordinated,​ of elevated neurodynamic organization during the patient preparation and surgery which were similar to those seen during simulation training, and which occurred near important episodes of the patient preparation and surgery. As the analyses moved down the neurodynamic hierarchy, and the simulation and live patient neurodynamics occurring during the intubation procedure were compared at progressively smaller time scales, differences emerged across scalp locations and EEG frequencies. The most significant was the pronounced suppression of gamma rhythms detected by the frontal scalp sensors during the live patient intubation which was absent in simulation trials of the intubation procedure. These results indicate that while profiles of the second-by-second neurodynamics of teams were similar in both the simulation and live patient environments,​ a deeper analysis revealed differences in the EEG frequencies and scalp locations of the signals responsible for those team dynamics. As measures of individual and team performance become more micro-scale and dynamic, and simulations become extended into virtual environments,​ these results argue for the need for parallel studies in live environments to validate the dynamics of cognition being observed."​
 +
 +===== Lundi 22 Juin 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Optimization of targeting specific areas by optimization of medical image processing methods based on deep learning"​ ====
 +Présenté par : Quoc-Anh Bui
 +
 +"​Transcranial Magnetic Stimulation treatment is a therapeutic technique that targets a specific area of the brain, in a non-invasive way. Individual positioning of the instruments for each patient improves the quality and effectiveness of the treatment. Therefore, improving the existing registration algorithm is necessary to improve the robustness, accuracy, reproducibility and preprocessing time of imaging data."
 +
 +===== Jeudi 18 Juin 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Person-Based Versus Generalized Impulsivity Disinhibition in Frontotemporal Dementia and Alzheimer Disease"​ ====
 +Présenté par : Delphine Tanguy
 +
 +"​Background:​ While much disinhibition in dementia results from generalized impulsivity,​ in behavioral variant frontotemporal
 +dementia (bvFTD) disinhibition may also result from impaired social cognition. Objective: To deconstruct disinhibition and its
 +neural correlates in bvFTD vs. early-onset Alzheimer’s disease (eAD). Methods: Caregivers of 16 bvFTD and 21 matched-eAD
 +patients completed the Frontal Systems Behavior Scale disinhibition items. The disinhibition items were further categorized into (1)
 +‘‘person-based’’ subscale which predominantly associated with violating social propriety and personal boundary and (2) ‘‘generalized impulsivity’’
 +subscale which included nonspecific impulsive acts. Subscale scores were correlated with grey matter volumes from
 +tensor-based morphometry on magnetic resonance images. Results: In comparison to the eAD patients, the bvFTD patients
 +developed greater person-based disinhibition (P < 0.001) but comparable generalized impulsivity. Severity of person-based disinhibition
 +significantly correlated with the left anterior superior temporal sulcus (STS), and generalized-impulsivity correlated with the
 +right orbitofrontal cortex (OFC) and the left anterior temporal lobe (aTL). Conclusions:​ Person-based disinhibition was predominant
 +in bvFTD and correlated with the left STS. In both dementia, violations of social propriety and personal boundaries
 +involved fronto-parieto-temporal network of Theory of Mind, whereas nonspecific disinhibition involved the OFC and aTL."
 +
 +===== Mardi 2 Juin 2020 15:00-16:00 =====
 +
 +==== "​Assessing scrub nurses'​ non-technical skills in a virtual and collaborative environement"​ ====
 +Présenté par : Marie-Stéphanie Bracq
 +
 +"This research is part of a multidisciplinary project to develop a virtual reality (VR) training environment in non-technical skills (NTS) for scrub nurses. The objective of this thesis was to provide the partners with the choice of NTS, to define training scenarios and to provide a first proof of concept on a targeted population.
 +According to the literature and interviews with expert scrub nurses, the NTS selected for the scenarios are situation awareness (SA) and speaking up.
 +Study 1, carried out with 13 scrub nurses and 16 non-experts,​ aims to assess the acceptability of the environment with the "​instrumentation table" scenario (under VR helmet).
 +Study 2, involving 18 scrub nursing students and 8 scrub nurses during an in-service course, aims to develop situation awareness, using the "​virtual operating room of errors"​ scenario (under VR helmet). This scenario enables SA to be assessed and seems a suitable training tool for this NTS.
 +Finally, Study 3, involving 33 scrub nursing students, aims to develop speaking up with a tablet scenario. Our results partially confirm the effect of status on the probability of speaking up and show an effect of status on the discomfort of speaking up.
 +Each study involved numerous exchanges with the project'​s VR engineers and scrub nursing teachers in order to allow the construction of the environment and its future integration into the scrub nursing school pedagogy. Finally, for each study, specific assessment tools were used and simulation sessions were developed according to recommendations with briefing, simulation, debriefing (HAS, 2012)."​
 +
 +===== Mardi 26 Mai 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Advancing Our Understandings of Healthcare Team Dynamics From the Simulation Room to the Operating Room: A Neurodynamic Perspective"​ ====
 +Présenté par : Thibaut Dognon
 +
 +"The initial models of team and team member dynamics using biometric data in healthcare will likely come from simulations. But how confident are we that the simulation-derived high-resolution dynamics will reflect those of teams working with live patients? We have developed neurodynamic models of a neurosurgery team while they performed a peroneal nerve decompression surgery on a patient to approach this question. The models were constructed from EEG-derived measures that provided second-by-second estimates of the neurodynamic responses of the team and team members to task uncertainty. The anesthesiologist and two neurosurgeons developed peaks, often coordinated,​ of elevated neurodynamic organization during the patient preparation and surgery which were similar to those seen during simulation training, and which occurred near important episodes of the patient preparation and surgery. As the analyses moved down the neurodynamic hierarchy, and the simulation and live patient neurodynamics occurring during the intubation procedure were compared at progressively smaller time scales, differences emerged across scalp locations and EEG frequencies. The most significant was the pronounced suppression of gamma rhythms detected by the frontal scalp sensors during the live patient intubation which was absent in simulation trials of the intubation procedure. These results indicate that while profiles of the second-by-second neurodynamics of teams were similar in both the simulation and live patient environments,​ a deeper analysis revealed differences in the EEG frequencies and scalp locations of the signals responsible for those team dynamics. As measures of individual and team performance become more micro-scale and dynamic, and simulations become extended into virtual environments,​ these results argue for the need for parallel studies in live environments to validate the dynamics of cognition being observed."​
 +
 +===== Mardi 26 Mai 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Connectivity predicts deep brain stimulation outcome in Parkinson Disease"​ ====
 +Présenté par : Alfonso Estudillo
 +
 +"​Objective:​ The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort.
 +
 +Methods: A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center.
 +
 +Results: In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p < 0.001). This same connectivity profile predicted response in an independent patient cohort (p < 0.01). Structural and functional connectivity were independent predictors of clinical improvement (p < 0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients.
 +
 +Interpretation:​ Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves."​
 +
 +===== Mardi 11 Mai 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Intraoperative Localization of STN During DBS Surgery Using a Data-Driven Model" ====
 +Présenté par : Thibault Martin
 +
 +"A new approach is presented for localizing the Subthalamic Nucleus (STN) during Deep 
Brain Stimulation (DBS) surgery based on microelectrode recordings (MERs). DBS is an accepted treatment for individuals living with Parkinson’s Disease (PD). This surgery involves implantation of a permanent electrode inside the STN to deliver electrical current. Since the STN is a very small region inside the brain, accurate placement of an electrode is a challenging task for the surgical team. Prior to placement of the permanent electrode, microelectrode recordings of brain activity are used intraoperatively to localize the STN. The placement of the electrode and the success of the therapy depend on this location. In this paper, ​ an objective approach is implemented to help the surgical team in localizing the STN. This is achieved by processing the MER signals and extracting features during the surgery to be used in a Machine Learning (ML) algorithm for defining the neurophysiological borders of the STN. For this purpose, a new classification approach is proposed with the goal of detecting both the dorsal and the ventral borders of the STN during the surgical procedure. Results collected from 100 PD patients in this study, show that by calculating and extracting wavelet transformation features from MER signals and using a data-driven computational deep neural network model, it is possible to detect the borders of the STN with an accuracy of 92%. The proposed method can be implemented in real-time during the surgery to model the neurophysiological nonlinearity along the path of the electrode trajectory during insertion."​
 +
 +===== Mardi 5 Mai 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Deep Double Descent: Where Bigger Models and More Data Hurt" ====
 +Présenté par : John Baxter
 +
 +"We show that a variety of modern deep learning tasks exhibit a "​double-descent"​ phenomenon where, as we increase model size, performance first gets worse and then gets better. Moreover, we show that double descent occurs not just as a function of model size, but also as a function of the number of training epochs. We unify the above phenomena by defining a new complexity measure we call the effective model complexity and conjecture a generalized double descent with respect to this measure. Furthermore,​ our notion of model complexity allows us to identify certain regimes where increasing (even quadrupling) the number of train samples actually hurts test performance."​
 +
 +===== Mardi 5 Mai 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Development of an Interactive Dashboard to Analyze Cognitive Workload of Surgical Teams During Complex Procedural Care" ====
 +Présenté par : Arnaud Huaulmé
 +
 +"In the surgical setting, team members constantly deal with a high-demand operative environment that requires simultaneously processing a large amount of information. In certain situations, high demands imposed by surgical tasks and other sources may exceed team member'​s cognitive capacity, leading to cognitive overload which may place patient safety at risk. In the present study, we describe a novel approach to integrate an objective measure of team member'​s cognitive load with procedural, behavioral and contextual data from real-life cardiac surgeries. We used heart rate variability analysis, capturing data simultaneously from multiple team members (surgeon, anesthesiologist and perfusionist) in a real-time and unobtrusive manner. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the analysis of the cognitive load imposed by specific steps, substeps and/or tasks. The described approach enables us to detect cognitive load fluctuations over time, under specific conditions (e.g., emergencies,​ teaching) and in situations that are prone to errors. This in-depth understanding of the relationship between cognitive load, task demands and error occurrence is essential for the development of cognitive support systems to recognize and mitigate errors during complex surgical care in the operating room."
 +
 +===== Mardi 28 Avril 2020 15:00-16:00 =====
 +
 +==== "Paper presentation : Biologically-inspired dynamical systems for movement generation: automatic real-time goal adaptation and obstacle avoidance"​ ====
 +Présenté par : Julien Berthelemy
 +
 +"​Dynamical systems can generate movement trajectories that are robust against perturbations. This article presents an improved modification of the original dynamic movement primitive (DMP) framework by Ijspeert et al [1], [2]. The new equations can generalize movements to new targets without singularities and large accelerations. Furthermore,​ the new equations can represent a movement in 3D task space without depending on the choice of coordinate system (invariance under invertible affine transformations). Our modified DMP is motivated from biological data (spinal-cord stimulation in frogs) and human behavioral experiments. We further extend the formalism to obstacle avoidance by exploiting the robustness against perturbations:​ an additional term is added to the differential equations to make the robot steer around an obstacle. This additional term empirically describes human obstacle avoidance. We demonstrate the feasibility of our approach using the Sarcos Slave robot arm: after learning a single placing movement, the robot placed a cup between two arbitrarily given positions and avoided approaching obstacles."​
 +
 +===== Mardi 14 Avril 2020 15:00-16:00 =====
 +
 +==== "​Academic background and PhD project"​ ====
 +Présenté par : Delphine Tanguy
 +
 +"A quick summary of my academic background followed by a presentation of my thesis project: the neural basis of disinhibition in neurodegenerative diseases. This will be a first introduction to my PhD project and a description of the protocols used, without any results presentation."​
 +
 +===== Mardi 7 Avril 2020 15:00-16:00 =====
 +
 +==== "​Overview of my past projects"​ ====
 +Présenté par : Alfonso Estudillo
 +
 +"In this meeting I am going to introduce a bit of myself, where I came from and what I did in my master and PhD theses. I am going to also show some projects I have involved with and finally the current project at MediCIS."​
 +
 +===== Vendredi 6 Mars 2020 13:00-14:00 =====
 +
 +==== "​History of Medecine, Study of medical and surgical knowledge and practices over time" ====
 +Présenté par : Alicia Diot
 +
 +"The History of Medicine is the study of medical and surgical knowledge and practices over time.
 +Thanks to the discoveries of traces of ancient medical knowledge, we understand that medical practice has always existed, the fight against pain and infirmity is as old as Humanity. What has evolved over the centuries are the means used in this fight, from magic to modern scanners, from shamans to specialized surgeons ...
 +Medicine is a discipline at the crossroads between Art and Science. From the origin of civilizations,​ it has been considered as an art, in the measure of intuition, empiricism, psychology ...
 +Over time and with progress, it has become a science, based on the understanding of the human and its pathologies,​ on the identification of therapeutics,​ and the discovery of new techniques.
 +Thus, while the art of healing is as old as mankind, Medicine as we know it today only dates back to the beginning of the 19th century. Since then, progress has continued at an impressive speed that keeps accelerating.
 +It therefore seems difficult to retrace the evolution of Medicine in an exhaustive way, however, I will outline the main stages and dominant discoveries that have given rise to today’s medicine.
 +It is important to understand that the division into chronological periods that I use in this presentation remains very artificial, the evolutions are actually very intertwined. Likewise, the great names that I cite as having largely contributed to the evolution of Medicine, are ultimately only a tiny part of the crowd that has participated in this evolution."​
 +
 +===== Mardi 11 Fevrier 2020 13:00-14:00 =====
 +
 +==== "​Topology-Aware Activation Layer for Neural Network Image Segmentation"​ ====
 +Présenté par : John Baxter
 +
 +"One of the recent developments in deep learning is the ability to train extremely deep residual neural networks, knowing that each residual block produces only marginal changes to the data. The accumulation of these changes result in the network'​s improved performance,​ analogous to a complex but trainable iterative algorithm. This intuition can be merged with the underlying theory of probabilistic graphical models in which these iterative algorithms are common and share the underlying probabilistic and information theoretic basis as deep learning. Prior models have been proposed with limitations on the number of iterations allowed in the solution algorithm due to the linear memory growth during the training process. This paper presents a structured activation layer which implements a conditional random field along with an arbitrary iteration message-passing marginal probability estimation algorithm which requires constant, rather than linear, memory with respect to the number of iterations. In this activation layer, the segmentation labels can be specified hierarchically,​ incorporating a level of abstract structure and some basic geometrical knowledge directly and easily into the network. Thus, this layer allows for the separation of abstract knowledge brought in by the network designer (in the form of the hierarchical structure) from probabilistic priors learned by the neural network. Preliminary results comparing this activation function to softmax and a similar non-hierarchical activation function indicate that it significantly improves performance in segmentation problems."​
 +
 +===== Mardi 11 Fevrier 2020 13:00-14:00 =====
 +
 +==== "​Localisation of the Subthalamic Nucleus in MRI via Convolution Neural Networks for Deep Brain Stimulation Planning"​ ====
 +Présenté par : John Baxter
 +
 +"Deep brain stimulation (DBS) is an interventional treatment for Parkinson'​s disease in which electrodes are placed into specific locations in the basal ganglia to alleviate symptoms such as tremor and dyskinesia. Due to the small size and low contrast of specific targets of interest, such as the subthalamic nucleus (STN), localisation of these structures from pre-operative MRI is of great value. These localisation approaches are often atlas-based,​ using registration algorithms to align patient images with a prior annotated atlas. However, these methods require a large amount of time, especially for correctly estimating deformation fields, or are prone to error for smaller structures such as the STN. This paper investigates two deep learning frameworks for the localisation of the stn from T1- and T2-weighted MRI using convolutional neural networks which estimate its centroid. These methods are compared against an atlas-based segmentation using the ParkMedAtlis v3 atlas, showing an improvement in localisation error in the range of ~0.5-1.3 mm with a reduction of orders of magnitude of computation time. This method of STN localisation will allow us in future to automatically identify the STN for DBS surgical planning as well as define a greatly reduced region-of-interest for more accurate segmentation of the STN."
 +
 +===== Mardi 28 Janvier 2020 13:00-14:00 =====
 +
 +==== "​Clinical and technological study of the spine biomechanics,​ scoliosis-oriented"​ ====
 +Présenté par : Kevin Le Mut
 +
 +"​Scoliosis is the largest three-dimensional deformation in the human body. It causes many health issues and there is a lack of data to correct them properly. Surgeons can only use their experience to operate. The role of biomechanics and finite element simulations is to provide more data and to analyze the constraints within the spine."​
 +
 +
 +===== Mardi 21 Janvier 2020 13:00-14:00 =====
 +
 +==== "​Convolutional Neural Network for Localizing the Subthalamic Nucleus Using One Second Micro-electrode Recordings"​ ====
 +Présenté par : Maxime Peralta
 +
 +"​Micro-electrode recording (MER) is a powerful way of localizing target structures during neurosurgical procedures such as the implantation of deep brain stimulation electrodes which is a common treatment for Parkinson'​s disease and other neurological disorders. Although allowing better clinical results than guiding only with per-operative imaging, MER is not unanimously used in clinic, notably because of its long duration which can lead to complications during the operation, and because it requries a high degree of expertise.
 +Different approaches towards automating MER analysis and structure localization have been proposed on the last decade, mainly focused on feature engineering. While the accuracies obtained are good in certain configurations,​ one issue with handcrafted features is that they do not necessarily capture more subtle differences in MER that are detected by expert neurophysiologists by ear. In this presentation,​ i'll show you a deep learning based pipeline for subthalamic nucleus (STN) localization with micro-electrode recordings which is motivated by the human auditory system. The proposed Convolutional Neural Network (CNN) shows improved accuracy over two comparative networks for locating the STN from one second MERs."
 +
 +===== Mardi 7 janvier 2020 13:00-14:00 =====
 +
 +==== "​Kinematic data analysis for skill assessment in surgery: a review"​ ====
 +Présenté par : Julien Berthelemy
 +
 +===== Mardi 22 Octobre 2019 13:00-14:00 =====
 +
 +==== "​Elephants in the Room:  How should we analyse trainee performance on simulator-based scenarios?"​ ====
 +Présenté par : Roy Eagleson
 +
 +===== Mardi 08 Octobre 2019 13:00-14:00 =====
 +
 +==== "What will happen to you if you go in medical device industry"​ ====
 +Présenté par : Ehouarn Maguet
 +
 +"I will share with you some part of the daily life of a software engineer in a medical device industry.
 +I will talk about medical standard (and try not to be boring), audit, impact of software and hardware on regulation, a resolution bug example, and some anecdotes."​
 +
 +===== Mardi 01 Octobre 2019 13:00-14:00 =====
 +
 +==== "​Cognitive Oriented Design and Assessment of Augmented Reality in Medicine"​ ====
 +Présenté par : Pierre Jannin
 +
 +"Mixed and Augmented Reality (AR) is a technology that aims to augment the perception of reality by adding computer-generated information. Such technology has been applied for medical procedures (especially surgery) the past 20 years to help physicians understand and perform procedures, as well as for training. However, as outlined in different review papers, AR has not yet reached its full potential usefulness and implementation in the medical workflow.
 +Many reasons for this have been expressed; one is that the AR system design approach is mainly technology driven, resulting in the need to develop relevant and clinically valuable AR applications. Another reason is the lack of relevant assessments of proposed AR systems to validate their benefits in all aspects of medical care. In this presentation,​ I will suggest a cognitive-oriented approach for both optimal design and assessment of AR systems. This approach is based on two main statements: (1) ensuring proper definition and modeling of medical objective(s) and (2) considering understanding as the main motivation for AR."
 +
 +===== Mardi 17 Septembre 2019 13:00-14:00 =====
 +
 +==== "​Augmented Reality Needle Guidance System and Multi-Modal Brain Connectivity Visualization for Pre-Surgical Planning"​ ====
 +Présenté par : Denis Kikinov
 +
 +"I will introduce my ongoing industrial project: a lightweight training simulator that allows clinicians and trainees to practise intramuscular injections. The system allows viewing of the underlying muscles when injecting with a syringe, provides EMG feedback and provides visual guidance in the case that the user wants to target a specific muscle. Our prototype is composed of a synthetic arm model (comprised of muscles, bones, simulated fat and skin), real syringes and needles, and android tablet, and a support frame. Although a prototype has been created, it has yet to be tested among clinicians.
 +In my presentation I will also introduce our new mobile device AR application based on data derived from advanced imaging processing of neuroimaging data for both a healthy brain, and one with a brain tumour. The application uses a multi-modal approach implementing the structural and functional connectivity of the specified patient’s anatomy and visualizes their brain in augmented reality. This approach allows the user to interact in real time with the neuroanatomy in the context of its associated SC and FC. The project is very lightweight,​ requiring only an Android device and a couple pieces of paper."​
 +
 +===== Mardi 10 Septembre 2019 13:00-14:00 =====
 +
 +==== "​Improving activity recognition based on a priori about surgeon biomechanical behavior"​ ====
 +Présenté par : Zakaria Kaddour
 +
 +"Robot assisted surgery has been a rising research field in the past few year with the introduction of the da Vinci Research Kit and similar tools and in order to supply better assistance the robot requires knowledge about the task performed by the surgeon. In this presentation I will talk about my previous work on the anatomy training VR platform and I move to talking about my current work which revolves around defining a constraint based on kinematic data collected from the surgeon during the surgery and use prior knowledge about the task as a whole and on the different gestures comprising it to improve activity recognition. This work can be done through the application of a LSTM deep learning model based on the kinematic data introduced with the priori."​
 +
 +===== Mardi 04 Juin 2019 13:00-14:00 =====
 +
 +==== "​Situation awareness in the “Virtual Operating Room of Errors”: a pilot study" ====
 +Présenté par : Marie-Stéphanie Bracq
 +
 +"​Training healthcare professionals in non-technical skills has revealed a crucial issue for patient safety and quality of care. Simulation offers good opportunities to follow that goal. Technologies for simulation are emerging, among which, virtual reality (VR). Yet, few VR simulators address non-technical skills. The “Virtual Operating Room of errors” scenario aims at training situation awareness in a VR environment."​
 +
 +===== Lundi 27 Mai 2019 13:00-14:00 =====
 +
 +==== "​Sub-cortical shape alteration analysis for automated Parkinson Disease Diagnosis with Machine Learning"​ ====
 +Présenté par : Maxime Peralta
 +
 +"Brain morphometry is still considered as a secondary source of information for the diagnosis of Parkinson Disease. Indeed, clinical teams mostly make their diagnosis with clinical biomarkers. However, the increasing accuracy of MRI acquisition encourages research toward finding reliable and easy to acquire morphometric biomarkers to diagnose, track and monitor the progression of the disease. Among the techniques explored to analyze the morphometric variations occurring in Parkinson Disease, shape analysis has proved itself more reliable and consistent than volume analysis, thickness analysis and volume analysis. Several studies tried to evaluate the significance of subcortical shape displacements as a diagnosis biomarker for Parkinson Disease, leading to often contradictory results.
 +
 +I will present you, in this noon sharing, a fully automated pipeline for sub-cortical alteration analysis involving, for the fist time in the litterature,​ machine learning. This pipeline is able to successfully classify several cohorts of PD patients with various disease severity, as well as an healthy control cohort, thus showing that crucial informations correlated to disease severity are embedded into bilateral caudate nucleus and putamen."​
 +
 +===== Mardi 14 Mai 2019 13:00-14:00 =====
 +
 +==== "​Overview of automatic classification methods to assess the skills of the surgeon during training using the kinematics data" ====
 +Présenté par : Julien Berthélemy
 +
 +"I will present a few studies about the automatic assessment of the surgeon'​s skills based on recordings of the kinematics data during a training exercice. Every article I will present uses a different method of machine learning or deep learning on the same JIGSAWS dataset. After that, I will compare the results of those classification methods and discuss them in order to develop my own method based on the ones giving the most promising results."​
 +
 +===== Mardi 30 Avril 2019 13:00-14:00 =====
 +
 +==== "How brain connectivity could help to predict DBS clinical outcomes ?" ====
 +Présenté par : Tristan Moreau
 +
 +"​Detailed anatomical knowledge and quantification of white matter properties are of particular therapeutic importance for Deep Brain Stimulation (DBS), an invasive neuromodulatory therapy which aims to balance disorganized motor circuits by applying high-frequency current to a target nucleus within basal ganglia. This presentation will take the form of a discussion around some interesting papers."​
 +
  
 ===== Mardi 02 Avril 2019 13:00-14:00 ===== ===== Mardi 02 Avril 2019 13:00-14:00 =====
inserm rennes1 ltsi