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Anne L Martel

Showing results (31-40 of 63) with videos related to

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IEEE Transactions on Medical Imaging|August 25, 2015
Triaging Diagnostically Relevant Regions from Pathology Whole Slides of Breast Cancer: A Texture Based ApproachMohammad Peikari, Mehrdad J Gangeh, Judit Zubovits, et al.
Medical Image Analysis|October 30, 2021
Self-supervised driven consistency training for annotation efficient histopathology image analysisChetan L Srinidhi, Seung Wook Kim, Fu-Der Chen, et al.
Biomedical Physics & Engineering Express|January 19, 2026
Model uncertainty estimates for deep learning mammographic density prediction using ordinal and classification approachesSteven Squires, Grey Kuling, D Gareth Evans, et al.
Magnetic Resonance in Medicine|April 22, 2003
Separating arterial and venous components from 3D dynamic contrast-enhanced MRI studies using factor analysisAnne L Martel, Doug Fraser, G Steve Delay, et al.
Journal of Digital Imaging|August 22, 2015
A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk WomenJacob E D Levman, Cristina Gallego-Ortiz, Ellen Warner, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|March 16, 2007
Piecewise-quadrilateral registration by optical flow--applications in contrast-enhanced MR imaging of the breastMichael S Froh, David C Barber, Kristy K Brock, et al.
Annals of Internal Medicine|January 16, 2002
Diagnosis of lower-limb deep venous thrombosis: a prospective blinded study of magnetic resonance direct thrombus imagingDouglas G W Fraser, Alan R Moody, Paul S Morgan, et al.
Scientific Reports|October 3, 2019
Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden AssessmentShazia Akbar, Mohammad Peikari, Sherine Salama, et al.
Scientific Reports|April 27, 2021
Overcoming the limitations of patch-based learning to detect cancer in whole slide imagesOzan Ciga, Tony Xu, Sharon Nofech-Mozes, et al.
NPJ Digital Medicine|November 7, 2025
A generalizable 3D framework and model for self-supervised learning in medical imagingTony Xu, Sepehr Hosseini, Chris Anderson, et al.
Pageof 7

Showing results (31-40 of 63) with videos related to

Sort By:
Pageof 7
IEEE Transactions on Medical Imaging|August 25, 2015
Triaging Diagnostically Relevant Regions from Pathology Whole Slides of Breast Cancer: A Texture Based ApproachMohammad Peikari, Mehrdad J Gangeh, Judit Zubovits, et al.
Medical Image Analysis|October 30, 2021
Self-supervised driven consistency training for annotation efficient histopathology image analysisChetan L Srinidhi, Seung Wook Kim, Fu-Der Chen, et al.
Biomedical Physics & Engineering Express|January 19, 2026
Model uncertainty estimates for deep learning mammographic density prediction using ordinal and classification approachesSteven Squires, Grey Kuling, D Gareth Evans, et al.
Magnetic Resonance in Medicine|April 22, 2003
Separating arterial and venous components from 3D dynamic contrast-enhanced MRI studies using factor analysisAnne L Martel, Doug Fraser, G Steve Delay, et al.
Journal of Digital Imaging|August 22, 2015
A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk WomenJacob E D Levman, Cristina Gallego-Ortiz, Ellen Warner, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|March 16, 2007
Piecewise-quadrilateral registration by optical flow--applications in contrast-enhanced MR imaging of the breastMichael S Froh, David C Barber, Kristy K Brock, et al.
Annals of Internal Medicine|January 16, 2002
Diagnosis of lower-limb deep venous thrombosis: a prospective blinded study of magnetic resonance direct thrombus imagingDouglas G W Fraser, Alan R Moody, Paul S Morgan, et al.
Scientific Reports|October 3, 2019
Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden AssessmentShazia Akbar, Mohammad Peikari, Sherine Salama, et al.
Scientific Reports|April 27, 2021
Overcoming the limitations of patch-based learning to detect cancer in whole slide imagesOzan Ciga, Tony Xu, Sharon Nofech-Mozes, et al.
NPJ Digital Medicine|November 7, 2025
A generalizable 3D framework and model for self-supervised learning in medical imagingTony Xu, Sepehr Hosseini, Chris Anderson, et al.
Pageof 7