Browsing by Subject "treatment planning"

A Deep-Learning Method of Automatic VMAT Planning via MLC Dynamic Sequence Prediction (AVP-DSP) Using 3D Dose Prediction: A Feasibility Study of Prostate Radiotherapy Application

Ni, Yimin (2020)

Introduction: VMAT treatment planning requires time-consuming DVH-based inverse optimization process, which impedes its application in time-sensitive situations. This work aims to develop a deep-learning based algorithm, ...

An Ensemble Approach to Knowledge-Based Intensity-Modulated Radiation Therapy Planning.

Zhang, Jiahan; Wu, Q Jackie; Xie, Tianyi; Sheng, Yang; Yin, Fang-Fang; Ge, Yaorong (Frontiers in oncology, 2018-01)

Knowledge-based planning (KBP) utilizes experienced planners' knowledge embedded in prior plans to estimate optimal achievable dose volume histogram (DVH) of new cases. In the regression-based KBP framework, previously planned ...

Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.

Wang, Wentao; Sheng, Yang; Wang, Chunhao; Zhang, Jiahan; Li, Xinyi; Palta, Manisha; Czito, Brian; ... (12 authors) (Frontiers in artificial intelligence, 2020-01)

Purpose: Treatment planning for pancreas stereotactic body radiation therapy (SBRT) is a difficult and time-consuming task. In this study, we aim to develop a novel deep learning framework to generate clinical-quality plans ...