Search Results - "Chang, Yankui"

A novel approach for eliminating metal artifacts based on MVCBCT and CycleGAN by Cao, Zheng, Gao, Xiang, Chang, Yankui, Liu, Gongfa, Pei, Yuanji

“…To develop a metal artifact reduction (MAR) algorithm and eliminate the adverse effects of metal artifacts on imaging diagnosis and radiotherapy dose…”
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Evaluation of deep learning‐based auto‐segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients by Wang, Zhi, Chang, Yankui, Peng, Zhao, Lv, Yin, Shi, Weijiong, Wang, Fan, Pei, Xi, Xu, X. George

“…Objective To evaluate the accuracy of a deep learning‐based auto‐segmentation mode to that of manual contouring by one medical resident, where both entities…”
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A method of using deep learning to predict three‐dimensional dose distributions for intensity‐modulated radiotherapy of rectal cancer by Zhou, Jieping, Peng, Zhao, Song, Yuchen, Chang, Yankui, Pei, Xi, Sheng, Liusi, Xu, X. George

“…Purpose To develop and test a three‐dimensional (3D) deep learning model for predicting 3D voxel‐wise dose distributions for intensity‐modulated radiotherapy…”
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Dosimetric comparison of deformable image registration and synthetic CT generation based on CBCT images for organs at risk in cervical cancer radiotherapy by Chang, Yankui, Liang, Yongguang, Yang, Bo, Qiu, Jie, Pei, Xi, Xu, Xie George

“…Anatomical variations existing in cervical cancer radiotherapy treatment can be monitored by cone-beam computed tomography (CBCT) images. Deformable image…”
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Clinical application of a GPU-accelerated monte carlo dose verification for cyberknife M6 with Iris collimator by Zhou, Peng, Chang, Yankui, Li, Shijun, Luo, Jia, Lei, Lin, Shang, Yufen, Pei, Xi, Ren, Qiang, Chen, Chuan

“…To apply an independent GPU-accelerated Monte Carlo (MC) dose verification for CyberKnife M6 with Iris collimator and evaluate the dose calculation accuracy of…”
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A Comparison Study Between CNN-Based Deformed Planning CT and CycleGAN-Based Synthetic CT Methods for Improving iCBCT Image Quality by Yang, Bo, Chang, Yankui, Liang, Yongguang, Wang, Zhiqun, Pei, Xi, Xu, Xie George, Qiu, Jie

“…The aim of this study is to compare two methods for improving the image quality of the Varian Halcyon cone-beam CT (iCBCT) system through the deformed planning…”
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Clinical application and improvement of a CNN‐based autosegmentation model for clinical target volumes in cervical cancer radiotherapy by Chang, Yankui, Wang, Zhi, Peng, Zhao, Zhou, Jieping, Pi, Yifei, Xu, X. George, Pei, Xi

“…Objective Clinical target volume (CTV) autosegmentation for cervical cancer is desirable for radiation therapy. Data heterogeneity and interobserver…”
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Prospects for daily online adaptive radiotherapy for cervical cancer: Auto-contouring evaluation and dosimetric outcomes by Zhang, Yu, Wang, Guangyu, Chang, Yankui, Wang, Zhiqun, Sun, Xiansong, Sun, Yuliang, Zeng, Zheng, Chen, Yining, Hu, Ke, Qiu, Jie, Yan, Junfang, Zhang, Fuquan

“…Training senior radiation therapists as "adapters" to manage influencers and target editing is critical in daily online adaptive radiotherapy (oART) for…”
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Innovative integration of augmented reality and optical surface imaging: A coarse‐to‐precise system for radiotherapy positioning by Zhang, Gongsen, Jiang, Zejun, Zhu, Jian, Dai, Tianyuan, He, Xiaolong, Liu, Xinchao, Chang, Yankui, Wang, Linlin

“…Background Traditional methods of radiotherapy positioning have shortcomings such as fragile skin‐markers, additional doses, and lack of information…”
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A prior‐information‐based automatic segmentation method for the clinical target volume in adaptive radiotherapy of cervical cancer by Wang, Xuanhe, Chang, Yankui, Pei, Xi, Xu, Xie George

“…Objective Adaptive planning to accommodate anatomic changes during treatment often requires repeated segmentation. In this study, prior patient‐specific data…”
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Adaptive assessment based on fractional CBCT images for cervical cancer by Chang, Yankui, Liang, Yongguang, Wu, Haotian, Li, Lingyan, Yang, Bo, Jiang, Lipeng, Ren, Qiang, Pei, Xi

“…Purpose Anatomical and other changes during radiotherapy will cause inaccuracy of dose distributions, therefore the expectation for online adaptive radiation…”
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Improving synthetic CT accuracy by combining the benefits of multiple normalized preprocesses by Cao, Zheng, Gao, Xiang, Chang, Yankui, Liu, Gongfa, Pei, Yuanji

“…Purpose To investigate the effect of different normalization preprocesses in deep learning on the accuracy of different tissues in synthetic computed…”
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Patient-Specific CT Doses Using DL-based Image Segmentation and GPU-based Monte Carlo Calculations for 10,281 Subjects by Ye, Zirui, Yao, Bei, Zheng, Haoran, Tao, Li, Wang, Ripeng, Chang, Yankui, Chen, Zhi, Zhao, Yingming, Wei, Wei, Xu, Xie George

“…Computed tomography (CT) scans are a major source of medical radiation exposure worldwide. In countries like China, the frequency of CT scans has grown…”
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OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines by 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…”
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