Research of Liver Segmentation Algorithm Based on High-Speed Complete Euclidean Distance Transformation and Statistical Analysis

Autor:	Yanan Zhang, Biao Zhang, Huiyan Jiang, Yi-xian Liu, Xi-he Gao, Mao Zong, Wei-peng Fan, Yuan-fei Li
Rok vydání:	2010
Předmět:	Computer science business.industry Segmentation-based object categorization Feature extraction Scale-space segmentation CAD Image segmentation body regions Euclidean distance Transformation (function) Medical imaging Computer vision Artificial intelligence business
Zdroj:	2010 International Conference on Biomedical Engineering and Computer Science.
DOI:	10.1109/icbecs.2010.5462332
Popis:	Liver segmentation is a prerequisite for liver cancer CAD, and the result of it affects the accuracy rate of feature extraction and recognition of liver cancer directly. Euclidean distance transformation is one of the main methods in medical image segmentation. However, simply using Euclidean distance transformation will lead to some problems, such as over-segmentation and excessively high cost of calculation. Therefore, this paper puts forward a new method of liver segmentation, which combines High-speed complete Euclidean distance transformation with statistical analysis. The effectiveness of this method has been verified after we apply it to the liver segmentation of abdominal liver CT images.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4e09201e8506e93d8a477ec42f2449b8 https://doi.org/10.1109/icbecs.2010.5462332 Zobrazit plný text záznamu