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Akademický článek

Deep learning based automatic segmentation of the Internal Pudendal Artery in definitive radiotherapy treatment planning of localized prostate cancer

Autor: Anjali Balagopal, Michael Dohopolski, Young Suk Kwon, Steven Montalvo, Howard Morgan, Ti Bai, Dan Nguyen, Xiao Liang, Xinran Zhong, Mu-Han Lin, Neil Desai, Steve Jiang

Publikováno v: Physics and Imaging in Radiation Oncology, Vol 30, Iss , Pp 100577- (2024)

Background and purpose: Radiation-induced erectile dysfunction (RiED) commonly affects prostate cancer patients, prompting clinical trials across institutions to explore dose-sparing to internal-pudendal-arteries (IPA) for preserving sexual potency.

Externí odkaz: https://doaj.org/article/7f81a560a5654c77b92d2fa77c809fe7

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Akademický článek

Performance deterioration of deep learning models after clinical deployment: a case study with auto-segmentation for definitive prostate cancer radiotherapy

Autor: Biling Wang, Michael Dohopolski, Ti Bai, Junjie Wu, Raquibul Hannan, Neil Desai, Aurelie Garant, Daniel Yang, Dan Nguyen, Mu-Han Lin, Robert Timmerman, Xinlei Wang, Steve B Jiang

Publikováno v: Machine Learning: Science and Technology, Vol 5, Iss 2, p 025077 (2024)

Our study aims to explore the long-term performance patterns for deep learning (DL) models deployed in clinic and to investigate their efficacy in relation to evolving clinical practices. We conducted a retrospective study simulating the clinical imp

Externí odkaz: https://doaj.org/article/c92535c3d5444875b45fe41667566894

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Improved Segmentation of Echocardiography With Orientation-Congruency of Optical Flow and Motion-Enhanced Segmentation

Autor: Wufeng Xue, Heng Cao, Junqiang Ma, Ti Bai, Tianfu Wang, Dong Ni

Publikováno v: IEEE Journal of Biomedical and Health Informatics. 26:6105-6115

Quantification of left ventricular (LV) ejection fraction (EF) from echocardiography depends upon the identification of endocardium boundaries as well as the calculation of end-diastolic (ED) and end-systolic (ES) LV volumes. It's critical to segment

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6837129b0594dc4358bd110f0a91d873
https://doi.org/10.1109/jbhi.2022.3221429

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Exploring dual-energy CT spectral information for machine learning-driven lesion diagnosis in pre-log domain

Autor: Shaojie Chang, Yongfeng Gao, Marc J. Pomeroy, Ti Bai, Hao Zhang, Siming Lu, Perry J. Pickhardt, Amit Gupta, Michael J. Reiter, Elaine S. Gould, Zhengrong Liang

Publikováno v: IEEE Trans Med Imaging

In this study, we proposed a computer-aided diagnosis (CADx) framework under dual-energy spectral CT (DECT), which operates directly on the transmission data in the pre-log domain, called CADxDE, to explore the spectral information for lesion diagnos

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::860e5a8d31c54c19b977488c58abd068
https://europepmc.org/articles/PMC10238622/

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Deep Learning based Direct Segmentation Assisted by Deformable Image Registration for Cone-Beam CT based Auto-Segmentation for Adaptive Radiotherapy

Autor: Xiao Liang, Howard Morgan, Ti Bai, Michael Dohopolski, Dan Nguyen, Steve Jiang

Cone-beam CT (CBCT)-based online adaptive radiotherapy calls for accurate auto-segmentation to reduce the time cost for physicians. However, deep learning (DL)-based direct segmentation of CBCT images is a challenging task, mainly due to the poor ima

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86efdec6507b457083f28641bc7cdb5c
http://arxiv.org/abs/2206.03413

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Akademický článek

Segmentation by test-time optimization for CBCT-based adaptive radiation therapy.

Autor: Xiao Liang, Jaehee Chun, Howard Morgan, Ti Bai, Dan Nguyen, Justin Park, Steve Jiang

Publikováno v: Medical Physics; Apr2023, Vol. 50 Issue 4, p1947-1961, 15p

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