A Physics-Guided Modular Deep-Learning Based Automated Framework for Tumor Segmentation in PET Images

Autor: Leung, Kevin H., Marashdeh, Wael, Wray, Rick, Ashrafinia, Saeed, Pomper, Martin G., Rahmim, Arman, Jha, Abhinav K.

The objective of this study was to develop a PET tumor-segmentation framework that addresses the challenges of limited spatial resolution, high image noise, and lack of clinical training data with ground-truth tumor boundaries in PET imaging. We prop

Externí odkaz: http://arxiv.org/abs/2002.07969

Deep learning and radiomics framework for PSMA-RADS classification of prostate cancer on PSMA PET.

Autor: Leung, Kevin H.^1,2 (AUTHOR) kleung8@jhmi.edu, Rowe, Steven P.^2,3 (AUTHOR), Leal, Jeffrey P.² (AUTHOR), Ashrafinia, Saeed² (AUTHOR), Sadaghiani, Mohammad S.² (AUTHOR), Chung, Hyun Woo⁴ (AUTHOR), Dalaie, Pejman² (AUTHOR), Tulbah, Rima² (AUTHOR), Yin, Yafu⁵ (AUTHOR), VanDenBerg, Ryan² (AUTHOR), Werner, Rudolf A.⁶ (AUTHOR), Pienta, Kenneth J.³ (AUTHOR), Gorin, Michael A.⁷ (AUTHOR), Du, Yong² (AUTHOR), Pomper, Martin G.^1,2,3 (AUTHOR)

Publikováno v: EJNMMI Research. 12/29/2022, Vol. 12 Issue 1, p1-15. 15p.

A three-stage, deep learning, ensemble approach for prognosis in patients with Parkinson's disease.

Autor: Leung, Kevin H.^1,2 (AUTHOR) kleung8@jhmi.edu, Rowe, Steven P.² (AUTHOR), Pomper, Martin G.^1,2 (AUTHOR), Du, Yong² (AUTHOR)

Publikováno v: EJNMMI Research. 6/7/2021, Vol. 11 Issue 1, p1-14. 14p.

Additional file 1 of A three-stage, deep learning, ensemble approach for prognosis in patients with Parkinson’s disease

Autor: Leung, Kevin H., Rowe, Steven P., Pomper, Martin G., Du, Yong

Additional file 1. Supplemental methods.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::034c85f845c1f99845ccf74d29360fb6