Automatic brain extraction and hemisphere segmentation in rat brain MR images after stroke using deformable models

被引:3
|
作者
Chang, Herng-Hua [1 ]
Yeh, Shin-Joe [2 ,3 ,4 ]
Chiang, Ming-Chang [5 ]
Hsieh, Sung-Tsang [2 ,3 ,4 ,6 ,7 ,8 ]
机构
[1] Natl Taiwan Univ, Dept Engn Sci & Ocean Engn, Computat Biomed Engn Lab CBEL, Taipei, Taiwan
[2] Natl Taiwan Univ, Grad Inst Anat & Cell Biol, Coll Med, Taipei 10051, Taiwan
[3] Natl Taiwan Univ Hosp, Dept Neurol, Taipei, Taiwan
[4] Natl Taiwan Univ Hosp, Stroke Ctr, Taipei, Taiwan
[5] Natl Yang Ming Chiao Tung Univ, Dept Biomed Engn, Taipei, Taiwan
[6] Natl Taiwan Univ, Grad Inst Clin Med, Coll Med, Taipei, Taiwan
[7] Natl Taiwan Univ, Grad Inst Brain & Mind Sci, Coll Med, Taipei, Taiwan
[8] Natl Taiwan Univ, Coll Med, Ctr Precis Med, Taipei, Taiwan
关键词
active contour model; DWI; level set; skull stripping; T2-weighted MRI; CEREBRAL HEMISPHERES; TISSUE SEGMENTATION; ISCHEMIC-STROKE; SURFACE; KURTOSIS; ATLAS;
D O I
10.1002/mp.15157
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose Experimental ischemic stroke models play an essential role in understanding the mechanisms of cerebral ischemia and evaluating the development of pathological extent. An important precursor to the investigation of ischemic strokes associated with rodents is the brain extraction and hemisphere segmentation in rat brain diffusion-weighted imaging (DWI) and T2-weighted MRI (T2WI) images. Accurate and reliable image segmentation tools for extracting the rat brain and hemispheres in the MR images are critical in subsequent processes, such as lesion identification and injury analysis. This study is an attempt to investigate rat brain extraction and hemisphere segmentation algorithms that are practicable in both DWI and T2WI images. Methods To automatically perform brain extraction, the proposed framework is based on an efficient geometric deformable model. By introducing an additional image force in response to the rat brain characteristics into the skull stripping model, we establish a unique rat brain extraction scheme in DWI and T2WI images. For the subsequent hemisphere segmentation, we develop an efficient brain feature detection algorithm to approximately separate the rat brain. A refinement process is enforced by constructing a gradient vector flow in the proximity of the midsurface, where a parametric active contour is attracted to achieve hemisphere segmentation. Results Extensive experiments with 55 DWI and T2WI subjects were executed in comparison with the state-of-the-art methods. Experimental results indicated that our rat brain extraction and hemisphere segmentation schemes outperformed the competitive methods and exhibited high performance both qualitatively and quantitatively. For rat brain extraction, the average Dice scores were 97.13% and 97.42% in DWI and T2WI image volumes, respectively. Rat hemisphere segmentation results based on the Hausdorff distance metric revealed average values of 0.17 and 0.15 mm for DWI and T2WI subjects, respectively. Conclusions We believe that the established frameworks are advantageous to facilitate preclinical stroke investigation and relevant neuroscience research that requires accurate brain extraction and hemisphere segmentation using rat DWI and T2WI images.
引用
收藏
页码:6036 / 6050
页数:15
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