Related Experiment Video
Updated: Dec 6, 2025

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
[Automated Pre-delineation of CTV in Patients with Cervical Cancer Using Dense V-Net]
Wen Guo1, Zhongjian Ju2, Wei Yang2
1School of Physics Science and Technology, Wuhan University, Wuhan, 430072.
Abstract:
We use a dense and fully connected convolutional network with good feature learning in small samples, to automatically pre-deline CTV of cervical cancer patients based on CT images and evaluate the effect. The CT data of stage IB and IIA postoperative cervical cancer with similar delineation scope were selected to be used to evaluate the pre-sketching accuracy from three aspects:sketching similarity, sketching offset and sketching volume difference. It has been proved that the 8 most representative parameters are superior to those with single network and reported internationally before. Dense V-Net can accurately predict CTV pre-delineation of cervical cancer patients, which can be used clinically after simple modification by doctors.

