This paper surveys the data‐driven dose prediction methods investigated for knowledge‐
based planning (KBP) in the last decade. These methods were classified into two major …

Treatment planning in radiation therapy has progressed enormously over the past several
decades. Such advancements came in the form of innovative hardware and algorithms …

Recent works in automated radiotherapy treatment planning have used machine learning
based on historical treatment plans to infer the spatial dose distribution for a novel patient …

Purpose: To ensure plan quality for adaptive IMRT of the prostate, we developed a
quantitative evaluation tool using a machine learning approach. This tool generates dose …

PURPOSE: To propose a method of intensity-modulated radiotherapy (IMRT) planning that
generates achievable dose–volume histogram (DVH) objectives using a database …

In this paper, we present a framework for detecting interest points in 3-D meshes and
computing their corresponding descriptors. For that, we propose an intrinsic scale detection …

US10475537B2 - Method and system for automated quality assurance and automated treatment
planning in radiation therapy - Google Patents US10475537B2 - Method and system for …

Radiation therapy is an integral part of cancer treatment, but to date it remains highly
manual. Plans are created through optimization of dose volume objectives that specify intent …

Automating the radiotherapy treatment planning process is a technically challenging
problem. The majority of automated approaches have focused on customizing and inferring …

Background and purpose Geometric information such as distance information is essential for
dose calculations in radiotherapy. However, state-of-the-art dose prediction methods use …