计算机科学
不变(物理)
人工智能
直方图
代表(政治)
匹配(统计)
翻译(生物学)
剂量体积直方图
放射治疗计划
计算机视觉
旋转(数学)
放射治疗
模式识别(心理学)
图像(数学)
医学
数学
放射科
病理
生物化学
化学
政治
信使核糖核酸
政治学
法学
数学物理
基因
作者
Michael Kazhdan,Patricio Simari,Todd McNutt,Binbin Wu,R. Jacques,Ming Chuang,Russell H. Taylor
标识
DOI:10.1007/978-3-642-04271-3_13
摘要
In this paper we address the challenge of matching patient geometry to facilitate the design of patient treatment plans in radiotherapy. To this end we propose a novel shape descriptor, the Overlap Volume Histogram, which provides a rotation and translation invariant representation of a patient's organs at risk relative to the tumor volume. Using our descriptor, it is possible to accurately identify database patients with similar constellations of organ and tumor geometries, enabling the transfer of treatment plans between patients with similar geometries, We demonstrate the utility of our method for such tasks by outperforming state of the art shape descriptors in the retrieval of patients with similar treatment plans. We also preliminarily show its potential as a quality control tool by demonstrating how it is used to identify an organ at risk whose dose can be significantly reduced.
科研通智能强力驱动
Strongly Powered by AbleSci AI