Research on con-beam CT images segmentation method

VernacularTitle:锥形束CT图像分割方法研究进展
Author: Ziyi WANG ¹ ; Jiawei SUN ; Sai ZHANG ; Heng ZHANG ; Xinye NI
Author Information

1. 南京医科大学附属常州第二人民医院放疗科　南京医科大学医学物理研究中心　江苏省医学物理工程研究中心，常州　213003
Keywords: Cone beam CT; Image segmentation; Deep learning
From: Chinese Journal of Radiological Medicine and Protection 2023;43(1):73-77
CountryChina
Language:Chinese
Abstract: Image-guided radiation therapy (IGRT) is a visual image-guided radiotherapy technique that has many advantages such as increasing the dose of tumor target area and reducing the dose of normal organ exposure. Cone beam CT (CBCT) is one of the most commonly used medical images in IGRT, and the rapid and accurate targeting of CBCT and the segmentation of dangerous organs are of great significance for radiotherapy. The current research method mainly includes partitioning method based on registration and segmentation method based on deep learning. This study reviews the CBCT image segmentation method, existing problems and development directions.