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Nathan Lay

Showing results (11-20 of 30) with videos related to

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Abdominal Radiology (New York)|February 12, 2024
Kidney scoring surveillance: predictive machine learning models for clear cell renal cell carcinoma growth using MRIPouria Yazdian Anari, Aryan Zahergivar, Nikhil Gopal, et al.
Journal of Medical Imaging (Bellingham, Wash.)|June 18, 2019
Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connectionsRuida Cheng, Nathan Lay, Holger R Roth, et al.
Journal of Medical Imaging (Bellingham, Wash.)|August 26, 2017
Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networksRuida Cheng, Holger R Roth, Nathan Lay, et al.
Academic Radiology|April 30, 2018
A Multireader Exploratory Evaluation of Individual Pulse Sequence Cancer Detection on Prostate Multiparametric Magnetic Resonance Imaging (MRI)Sonia Gaur, Stephanie Harmon, Rajan T Gupta, et al.
Medical Physics|March 1, 2023
Deep learning-based decision forest for hereditary clear cell renal cell carcinoma segmentation on MRINathan Lay, Pouria Yazdian Anari, Aditi Chaurasia, et al.
Journal of Medical Imaging (Bellingham, Wash.)|August 14, 2025
Physician-guided deep learning model for assessing thymic epithelial tumor volumeNirmal Choradia, Nathan Lay, Alex Chen, et al.
Abdominal Radiology (New York)|January 31, 2022
Deep learning-based artificial intelligence for prostate cancer detection at biparametric MRISherif Mehralivand, Dong Yang, Stephanie A Harmon, et al.
Abdominal Radiology (New York)|July 22, 2022
An MRI-based radiomics model to predict clear cell renal cell carcinoma growth rate classes in patients with von Hippel-Lindau syndromePouria Yazdian Anari, Nathan Lay, Nikhil Gopal, et al.
Arxiv|February 15, 2023
Automatic segmentation of clear cell renal cell tumors, kidney, and cysts in patients with von Hippel-Lindau syndrome using U-net architecture on magnetic resonance imagesPouria Yazdian Anari, Nathan Lay, Aditi Chaurasia, et al.
Computers in Biology and Medicine|March 24, 2025
Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohortsFahmida Haque, Alex Chen, Nathan Lay, et al.
Pageof 3

Showing results (11-20 of 30) with videos related to

Sort By:
Pageof 3
Abdominal Radiology (New York)|February 12, 2024
Kidney scoring surveillance: predictive machine learning models for clear cell renal cell carcinoma growth using MRIPouria Yazdian Anari, Aryan Zahergivar, Nikhil Gopal, et al.
Journal of Medical Imaging (Bellingham, Wash.)|June 18, 2019
Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connectionsRuida Cheng, Nathan Lay, Holger R Roth, et al.
Journal of Medical Imaging (Bellingham, Wash.)|August 26, 2017
Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networksRuida Cheng, Holger R Roth, Nathan Lay, et al.
Academic Radiology|April 30, 2018
A Multireader Exploratory Evaluation of Individual Pulse Sequence Cancer Detection on Prostate Multiparametric Magnetic Resonance Imaging (MRI)Sonia Gaur, Stephanie Harmon, Rajan T Gupta, et al.
Medical Physics|March 1, 2023
Deep learning-based decision forest for hereditary clear cell renal cell carcinoma segmentation on MRINathan Lay, Pouria Yazdian Anari, Aditi Chaurasia, et al.
Journal of Medical Imaging (Bellingham, Wash.)|August 14, 2025
Physician-guided deep learning model for assessing thymic epithelial tumor volumeNirmal Choradia, Nathan Lay, Alex Chen, et al.
Abdominal Radiology (New York)|January 31, 2022
Deep learning-based artificial intelligence for prostate cancer detection at biparametric MRISherif Mehralivand, Dong Yang, Stephanie A Harmon, et al.
Abdominal Radiology (New York)|July 22, 2022
An MRI-based radiomics model to predict clear cell renal cell carcinoma growth rate classes in patients with von Hippel-Lindau syndromePouria Yazdian Anari, Nathan Lay, Nikhil Gopal, et al.
Arxiv|February 15, 2023
Automatic segmentation of clear cell renal cell tumors, kidney, and cysts in patients with von Hippel-Lindau syndrome using U-net architecture on magnetic resonance imagesPouria Yazdian Anari, Nathan Lay, Aditi Chaurasia, et al.
Computers in Biology and Medicine|March 24, 2025
Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohortsFahmida Haque, Alex Chen, Nathan Lay, et al.
Pageof 3