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members:john.baxter:index [2018/03/09 13:58] jbaxter |
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- | <html> <div class="pageTitle"> John BAXTER </div></html> | + | <html> <div class="John BAXTER"> John BAXTER </div></html> |
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====== Contact ====== | ====== Contact ====== | ||
+ | {{ :members:john.baxter:johnbaxter.jpg?140}} | ||
**Email** : jbaxter@univ-rennes1.fr \\ | **Email** : jbaxter@univ-rennes1.fr \\ | ||
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CS 34317\\ | CS 34317\\ | ||
35043 Rennes cedex - France\\ | 35043 Rennes cedex - France\\ | ||
- | **Phone** : +33 2 23 23 38 29\\ | ||
**Assistant** : Noemie Buisard : +33 2 23 23 47 18\\ | **Assistant** : Noemie Buisard : +33 2 23 23 47 18\\ | ||
====== Publications ====== | ====== Publications ====== | ||
[[https://scholar.google.ca/citations?user=zB8zUmYAAAAJ&hl=en&oi=ao|Google Scholar]] | [[https://scholar.google.ca/citations?user=zB8zUmYAAAAJ&hl=en&oi=ao|Google Scholar]] | ||
+ | |||
+ | [[https://www.researchgate.net/profile/John_Baxter5|ResearchGate]] | ||
====== Research areas ====== | ====== Research areas ====== | ||
- | Medical image processing, human interaction with artificial intelligence, machine learning, variational-optimization in image segmentation | + | Medical image processing, human interaction with machine intelligence, machine learning, variational-optimization in image segmentation |
+ | |||
+ | ====== Research objectives ====== | ||
+ | My current research concerns how clinicians interact with machine intelligence to define and solve complex problems in medical image processing. This work extends from my [[https://ir.lib.uwo.ca/etd/4602/|PhD thesis]] in developing variational optimization algorithms for medical image processing which allow clinical users to more readily describe the properties of the image and structure of the anatomy being imaged. (I completed my PhD in The Virtual Augmentation and Simulation for Surgery and Therapy (VASST) laboratory at the Robarts Research Institute in London, Ontario, Canada. You can view my former PhD page at [[http://www.imaging.robarts.ca/petergrp/jbaxter|VASST]].) | ||
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+ | I am interesting developing solutions in machine learning that allow for easier and more nuanced communication of complex information between the computer and the clinical user. This focus includes technical development in areas such as medical image processing, visualization and deep learning, but also extends to more theoretically-oriented in semiotic human-computer interaction. (For an example of the latter, please read my paper on [[http://www.medicalimageanalysisjournal.com/article/S1361-8415(17)30176-7/abstract|The Semiotics of Medical Image Segmentation]] recently published in //Medical Image Analysis//.) |