Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy

Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy

Objective: To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. Methods: 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the CycleGAN, Pix2pix and U-Net models we...

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Autores principales: Xudong Xue PhD, Yi Ding PhD, Jun Shi MS, Xiaoyu Hao MS, Xiangbin Li PhD, Dan Li MS, Yuan Wu PhD, Hong An PhD, Man Jiang PhD, Wei Wei PhD, Xiao Wang PhD
Formato: article
Lenguaje:EN
Publicado: SAGE Publishing 2021
Materias:
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
Acceso en línea:https://doaj.org/article/7da452e2c3014ae69531093403bf9961
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https://doaj.org/article/7da452e2c3014ae69531093403bf9961

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