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pro vyhledávání: '"Siebers, Jeffrey"'
Autor:
Rashad, M. N. H., Karki, Abishek, Czak, Jason, Alves, Victor Gabriel, Nourzadeh, Hamidreza, Choi, Wookjin, Siebers, Jeffrey V
Purpose: This study quantifies the variation in dose-volume histogram (DVH) and normal tissue complication probability (NTCP) metrics for head-and-neck (HN) cancer patients when alternative organ-at-risk (OAR) delineations are used for treatment plan
Externí odkaz:
http://arxiv.org/abs/2401.05656
Autor:
Babier, Aaron, Mahmood, Rafid, Zhang, Binghao, Alves, Victor G. L., Barragán-Montero, Ana Maria, Beaudry, Joel, Cardenas, Carlos E., Chang, Yankui, Chen, Zijie, Chun, Jaehee, Diaz, Kelly, Eraso, Harold David, Faustmann, Erik, Gaj, Sibaji, Gay, Skylar, Gronberg, Mary, Guo, Bingqi, He, Junjun, Heilemann, Gerd, Hira, Sanchit, Huang, Yuliang, Ji, Fuxin, Jiang, Dashan, Giraldo, Jean Carlo Jimenez, Lee, Hoyeon, Lian, Jun, Liu, Shuolin, Liu, Keng-Chi, Marrugo, José, Miki, Kentaro, Nakamura, Kunio, Netherton, Tucker, Nguyen, Dan, Nourzadeh, Hamidreza, Osman, Alexander F. I., Peng, Zhao, Muñoz, José Darío Quinto, Ramsl, Christian, Rhee, Dong Joo, Rodriguez, Juan David, Shan, Hongming, Siebers, Jeffrey V., Soomro, Mumtaz H., Sun, Kay, Hoyos, Andrés Usuga, Valderrama, Carlos, Verbeek, Rob, Wang, Enpei, Willems, Siri, Wu, Qi, Xu, Xuanang, Yang, Sen, Yuan, Lulin, Zhu, Simeng, Zimmermann, Lukas, Moore, Kevin L., Purdie, Thomas G., McNiven, Andrea L., Chan, Timothy C. Y.
We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients with head-and-neck cancer and high-quality dose predictions from 19 KBP
Externí odkaz:
http://arxiv.org/abs/2202.08303
$\textbf{Purpose:}$ To quantify the effectiveness of EPID-based cine transmission dosimetry to detect gross patient anatomic errors. $\textbf{Method and Materials:}$ EPID image frames resulting from fluence transmitted through multiple patients anato
Externí odkaz:
http://arxiv.org/abs/2111.06489
Autor:
Soomro, Mumtaz Hussain, Alves, Victor Gabriel Leandro, Nourzadeh, Hamidreza, Siebers, Jeffrey V.
The DeepDoseNet 3D dose prediction model based on ResNet and Dilated DenseNet is proposed. The 340 head-and-neck datasets from the 2020 AAPM OpenKBP challenge were utilized, with 200 for training, 40 for validation, and 100 for testing. Structures in
Externí odkaz:
http://arxiv.org/abs/2111.00077
Autor:
Soomro, Mumtaz Hussain, Nourzadeh, Hamidreza, Alves, Victor Gabriel Leandro, Choi, Wookjin, Siebers, Jeffrey V.
A 3D deep learning model (OARnet) is developed and used to delineate 28 H&N OARs on CT images. OARnet utilizes a densely connected network to detect the OAR bounding-box, then delineates the OAR within the box. It reuses information from any layer to
Externí odkaz:
http://arxiv.org/abs/2108.13987
Akademický článek
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Autor:
Aliotta, Eric, Nourzadeh, Hamidreza, Choi, Wookjin, Leandro Alves, Victor Gabriel, Siebers, Jeffrey V.
Publikováno v:
In Advances in Radiation Oncology November-December 2020 5(6):1324-1333
Publikováno v:
In Advances in Radiation Oncology March-April 2020 5(2):279-288
Autor:
Siebers, Jeffrey Vincent.
Thesis (Ph. D.)--University of Wisconsin--Madison, 1990.
Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 153(i.e. 154)-163).
Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 153(i.e. 154)-163).
Externí odkaz:
http://catalog.hathitrust.org/api/volumes/oclc/22612152.html
Publikováno v:
In Radiotherapy and Oncology November 2017 125(2):344-350