Výsledky vyhledávání - "Siebers, Jeffrey V"

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Divergent Clinical Equivalence Findings from DVH and NTCP Metrics for Alternative OAR Delineations with Increasing Setup Variability in Head-and-Neck Radiotherapy

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

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OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines

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

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DeepDoseNet: A Deep Learning model for 3D Dose Prediction in Radiation Therapy

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

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OARnet: Automated organs-at-risk delineation in Head and Neck CT images

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

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