Patch-Based Label Fusion for Automatic Multi-Atlas-Based Prostate Segmentation in MR Images

被引：2
|
作者：
Yang, Xiaofeng [1 ,2 ]
Jani, Ashesh B. [1 ,2 ]
Rossi, Peter J. [1 ,2 ]
Mao, Hui [2 ,3 ]
Curran, Walter J. [1 ,2 ]
Liu, Tian [1 ,2 ]
机构：
[1] Emory Univ, Dept Radiat Oncol, Atlanta, GA 30322 USA
[2] Emory Univ, Winship Canc Inst, Atlanta, GA 30322 USA
[3] Emory Univ, Dept Radiol & Imaging Sci, Atlanta, GA 30322 USA
来源：
MEDICAL IMAGING 2016: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING | 2016年 / 9786卷
关键词：
Prostate segmentation; MRI; multi-atlas; label fusion; prostate cancer; REGISTRATION; CANCER;
D O I：
10.1117/12.2216424
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In this paper, we propose a 3D multi-atlas-based prostate segmentation method for MR images, which utilizes patch-based label fusion strategy. The atlases with the most similar appearance are selected to serve as the best subjects in the label fusion. A local patch-based atlas fusion is performed using voxel weighting based on anatomical signature. This segmentation technique was validated with a clinical study of 13 patients and its accuracy was assessed using the physicians' manual segmentations (gold standard). Dice volumetric overlapping was used to quantify the difference between the automatic and manual segmentation. In summary, we have developed a new prostate MR segmentation approach based on nonlocal patch-based label fusion, demonstrated its clinical feasibility, and validated its accuracy with manual segmentations.
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收藏
页数：7
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