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Journal of Medical Imaging (Bellingham, Wash.)
|
March 10, 2023
CROPro: a tool for automated cropping of prostate magnetic resonance images
Alexandros Patsanis, Mohammed R S Sunoqrot, Tone F Bathen, et al.
Insights Into Imaging
|
September 25, 2023
Label-set impact on deep learning-based prostate segmentation on MRI
Jakob Meglič, Mohammed R S Sunoqrot, Tone Frost Bathen, et al.
European Radiology Experimental
|
July 31, 2022
Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges
Mohammed R S Sunoqrot, Anindo Saha, Matin Hosseinzadeh, et al.
Magma (New York, N.Y.)
|
August 2, 2020
Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition
Mohammed R S Sunoqrot, Gabriel A Nketiah, Kirsten M Selnæs, et al.
Diagnostics (Basel, Switzerland)
|
September 28, 2021
The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images
Mohammed R S Sunoqrot, Kirsten M Selnæs, Elise Sandsmark, et al.
Methods in Molecular Biology (Clifton, N.J.)
|
March 17, 2017
High Resolution Microultrasound (μUS) Investigation of the Gastrointestinal (GI) Tract
Thineskrishna Anbarasan, Christine E M Démoré, Holly Lay, et al.
Insights Into Imaging
|
January 26, 2026
Prospective validation of an AI software for detecting clinically significant prostate cancer on biparametric MRI
Mohammed R S Sunoqrot, Rebecca Segre, Gabriel A Nketiah, et al.
Diagnostics (Basel, Switzerland)
|
September 23, 2020
A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI
Mohammed R S Sunoqrot, Kirsten M Selnæs, Elise Sandsmark, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
December 4, 2019
Relative Enhanced Diffusivity in Prostate Cancer: Protocol Optimization and Diagnostic Potential
Daniel C Billdal, Peter T While, Kirsten M Selnaes, et al.
Radiology. Artificial Intelligence
|
July 30, 2025
Optimizing Federated Learning Configurations for MRI Prostate Segmentation and Cancer Detection: A Simulation Study
Ashkan Moradi, Fadila Zerka, Joeran Sander Bosma, et al.
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Search research articles
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Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Journal of Medical Imaging (Bellingham, Wash.)
|
March 10, 2023
CROPro: a tool for automated cropping of prostate magnetic resonance images
Alexandros Patsanis, Mohammed R S Sunoqrot, Tone F Bathen, et al.
Insights Into Imaging
|
September 25, 2023
Label-set impact on deep learning-based prostate segmentation on MRI
Jakob Meglič, Mohammed R S Sunoqrot, Tone Frost Bathen, et al.
European Radiology Experimental
|
July 31, 2022
Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges
Mohammed R S Sunoqrot, Anindo Saha, Matin Hosseinzadeh, et al.
Magma (New York, N.Y.)
|
August 2, 2020
Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition
Mohammed R S Sunoqrot, Gabriel A Nketiah, Kirsten M Selnæs, et al.
Diagnostics (Basel, Switzerland)
|
September 28, 2021
The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images
Mohammed R S Sunoqrot, Kirsten M Selnæs, Elise Sandsmark, et al.
Methods in Molecular Biology (Clifton, N.J.)
|
March 17, 2017
High Resolution Microultrasound (μUS) Investigation of the Gastrointestinal (GI) Tract
Thineskrishna Anbarasan, Christine E M Démoré, Holly Lay, et al.
Insights Into Imaging
|
January 26, 2026
Prospective validation of an AI software for detecting clinically significant prostate cancer on biparametric MRI
Mohammed R S Sunoqrot, Rebecca Segre, Gabriel A Nketiah, et al.
Diagnostics (Basel, Switzerland)
|
September 23, 2020
A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI
Mohammed R S Sunoqrot, Kirsten M Selnæs, Elise Sandsmark, et al.
Journal of Magnetic Resonance Imaging : JMRI
|
December 4, 2019
Relative Enhanced Diffusivity in Prostate Cancer: Protocol Optimization and Diagnostic Potential
Daniel C Billdal, Peter T While, Kirsten M Selnaes, et al.
Radiology. Artificial Intelligence
|
July 30, 2025
Optimizing Federated Learning Configurations for MRI Prostate Segmentation and Cancer Detection: A Simulation Study
Ashkan Moradi, Fadila Zerka, Joeran Sander Bosma, et al.
Page
of 2