Document Detail

Automatic model-based contour detection of left ventricle myocardium from cardiac CT images.
MedLine Citation:
PMID:  22547333     Owner:  NLM     Status:  Publisher    
PURPOSE: For accurate evaluation of myocardial perfusion on computed tomography images, precise identification of the myocardial borders of the left ventricle (LV) is mandatory. In this article, we propose a method to detect the contour of LV myocardium automatically and accurately. METHODS: Our detection method is based on active shape model. For precise detection, we estimate the pose and shape parameters separately by three steps: LV coordinate system estimation, myocardial shape estimation, and transformation. In LV coordinate system estimation, we detect heart features followed by the entire LV by introducing machine-learning approach. Since the combination of two types feature detection covers the LV variation, such as pose or shape, we can estimate the LV coordinate system robustly. In myocardial shape estimation, we minimize the energy function including pattern error around myocardium with adjustment of pattern model to input image using estimated concentration of contrast dye. Finally, we detect LV myocardial contours in the input images by transforming the estimated myocardial shape using the matrix composed of the vectors calculated by the LV coordinate system estimation. RESULTS: In our experiments with 211 images from 145 patients, mean myocardial contours point-to-point errors for our method as compared to ground truth were 1.02 mm for LV endocardium and 1.07 mm for LV epicardium. The average computation time was 2.4 s (on a 3.46 GHz processor with 2-multithreading process). CONCLUSIONS: Our method achieved accurate and fast myocardial contour detection which may be sufficient for myocardial perfusion examination.
Takamasa Sugiura; Tomoyuki Takeguchi; Yukinobu Sakata; Shuhei Nitta; Tomoya Okazaki; Nobuyuki Matsumoto; Yasuko Fujisawa
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-5-1
Journal Detail:
Title:  International journal of computer assisted radiology and surgery     Volume:  -     ISSN:  1861-6429     ISO Abbreviation:  -     Publication Date:  2012 May 
Date Detail:
Created Date:  2012-5-1     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101499225     Medline TA:  Int J Comput Assist Radiol Surg     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Multimedia Laboratory, Corporate Research and Development Center, Toshiba Corporation, 1 Komukaitoshiba-cho, Saiwai-ku, Kawasaki, Kanagawa, 212-8582, Japan,
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