In this study, we propose a state-of-the-art automated segmentation of OAR using a multi-output support vector regression (MSVR) machine learning algorithm to ...
Mar 12, 2018 · In this study, we propose a state-of-the-art automated segmentation of OAR using a multi-output support vector regression (MSVR) machine ...
ABSTRACT. Accurate segmentation of organs-at-risk (OAR) is essential for treatment planning of head and neck (HaN) cancers. A desire to shift from manual ...
Automated delineation of organs-at-risk in head and neck CT images using multi-output support vector regression · Medicine, Engineering. Medical Imaging · 2018.
A 3D deep learning model (OARnet) is developed and used to delineate 28 H&N OARs on CT images. OARnet utilizes a densely connected network to detect the OAR ...
Fully automatic multi-organ segmentation for head and neck cancer radiotherapy ... Automated delineation of organs-at-risk in head and neck CT images using ...
Purpose. Accurate segmentation of organs‐at‐risks (OARs) is the key step for efficient planning of radiation therapy for head and neck (HaN) cancer ...
Missing: regression. | Show results with:regression.
This study aimed to develop a deep learning-based automated OAR delineation method to tackle the current challenges remaining in achieving reliable expert ...
Missing: output support vector regression.
Automated delineation of organs-at-risk in head and neck ct images using multi-output support vector regression. Paper presented at: Medical Imaging. 2018 ...
Automated delineation of organs-at-risk in head and neck CT images using multi-output support vector regression · Clara M. TamXiaofeng YangS. TianXi JiangJ ...