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John S H Baxter

Showing results (1-10 of 35) with videos related to

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Journal of Medical Imaging (Bellingham, Wash.)|July 15, 2022
Combining simple interactivity and machine learning: a separable deep learning approach to subthalamic nucleus localization and segmentation in MRI for deep brain stimulation surgical planningJohn S H Baxter, Pierre Jannin
Computer Assisted Surgery (Abingdon, England)|February 8, 2022
Bias in machine learning for computer-assisted surgery and medical image processingJohn S H Baxter, Pierre Jannin
Medical Image Analysis|February 28, 2025
Exploring the values underlying machine learning research in medical image analysisJohn S H Baxter, Roy Eagleson
Artificial Intelligence in Medicine|November 26, 2021
Machine learning in deep brain stimulation: A systematic reviewMaxime Peralta, Pierre Jannin, John S H Baxter
International Journal of Computer Assisted Radiology and Surgery|October 10, 2023
A preliminary exploration into top-down and bottom-up deep-learning approaches to localising neuro-interventional point targets in volumetric MRIEnora Giffard, Pierre Jannin, John S H Baxter
International Journal of Computer Assisted Radiology and Surgery|July 1, 2024
Generalisation capabilities of machine-learning algorithms for the detection of the subthalamic nucleus in micro-electrode recordingsThibault Martin, Pierre Jannin, John S H Baxter
Artificial Intelligence in Medicine|April 20, 2021
Data imputation and compression for Parkinson's disease clinical questionnairesMaxime Peralta, Pierre Jannin, Claire Haegelen, et al.
International Journal of Computer Assisted Radiology and Surgery|July 3, 2021
PassFlow: a multimodal workflow for predicting deep brain stimulation outcomesMaxime Peralta, Claire Haegelen, Pierre Jannin, et al.
Medical Image Analysis|December 1, 2017
The semiotics of medical image SegmentationJohn S H Baxter, Eli Gibson, Roy Eagleson, et al.
IEEE Transactions on Medical Imaging|February 7, 2018
Cyclic Continuous Max-Flow: A Third Paradigm in Generating Local Phase Shift Maps in MRIJohn S H Baxter, Zahra Hosseini, Terry M Peters, et al.
Pageof 4

Showing results (1-10 of 35) with videos related to

Sort By:
Pageof 4
Journal of Medical Imaging (Bellingham, Wash.)|July 15, 2022
Combining simple interactivity and machine learning: a separable deep learning approach to subthalamic nucleus localization and segmentation in MRI for deep brain stimulation surgical planningJohn S H Baxter, Pierre Jannin
Computer Assisted Surgery (Abingdon, England)|February 8, 2022
Bias in machine learning for computer-assisted surgery and medical image processingJohn S H Baxter, Pierre Jannin
Medical Image Analysis|February 28, 2025
Exploring the values underlying machine learning research in medical image analysisJohn S H Baxter, Roy Eagleson
Artificial Intelligence in Medicine|November 26, 2021
Machine learning in deep brain stimulation: A systematic reviewMaxime Peralta, Pierre Jannin, John S H Baxter
International Journal of Computer Assisted Radiology and Surgery|October 10, 2023
A preliminary exploration into top-down and bottom-up deep-learning approaches to localising neuro-interventional point targets in volumetric MRIEnora Giffard, Pierre Jannin, John S H Baxter
International Journal of Computer Assisted Radiology and Surgery|July 1, 2024
Generalisation capabilities of machine-learning algorithms for the detection of the subthalamic nucleus in micro-electrode recordingsThibault Martin, Pierre Jannin, John S H Baxter
Artificial Intelligence in Medicine|April 20, 2021
Data imputation and compression for Parkinson's disease clinical questionnairesMaxime Peralta, Pierre Jannin, Claire Haegelen, et al.
International Journal of Computer Assisted Radiology and Surgery|July 3, 2021
PassFlow: a multimodal workflow for predicting deep brain stimulation outcomesMaxime Peralta, Claire Haegelen, Pierre Jannin, et al.
Medical Image Analysis|December 1, 2017
The semiotics of medical image SegmentationJohn S H Baxter, Eli Gibson, Roy Eagleson, et al.
IEEE Transactions on Medical Imaging|February 7, 2018
Cyclic Continuous Max-Flow: A Third Paradigm in Generating Local Phase Shift Maps in MRIJohn S H Baxter, Zahra Hosseini, Terry M Peters, et al.
Pageof 4