Local SIMPLE Multi Atlas-Based Segmentation Applied to Lung Lobe Detection on Chest CT

被引：5

作者：

Agarwal, M. ^{[1
,2
]}

Hendriks, E. A. ^{[2
]}

Stoel, B. C. ^{[1
]}

Bakker, M. E. ^{[1
]}

Reiber, J. H. C. ^{[1
]}

Staring, M. ^{[1
]}

机构：

[1] Leiden Univ, Med Ctr, Leiden, Netherlands

[2] Delft Univ Technol, Delft, Netherlands

来源：

MEDICAL IMAGING 2012: IMAGE PROCESSING | 2012年 / 8314卷

关键词：

multi atlas-based segmentation; SIMPLE; local; multi-label; registration; IMAGE SEGMENTATION; COMBINATION; STRATEGIES;

D O I：

10.1117/12.911552

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

For multi atlas-based segmentation approaches, a segmentation fusion scheme which considers local performance measures may be more accurate than a method which uses a global performance measure. We improve upon an existing segmentation fusion method called SIMPLE and extend it to be localized and suitable for multi-labeled segmentations. We demonstrate the algorithm performance on 23 CT scans of COPD patients using a leave-one-out experiment. Our algorithm performs significantly better (p < 0.01) than majority voting, STAPLE, and SIMPLE, with a median overlap of the fissure of 0.45, 0.48, 0.55 and 0.6 for majority voting, STAPLE, SIMPLE, and the proposed algorithm, respectively.

引用

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