Title :
A curvelet-based morphological segmentation of abdominal CT images
Author :
Sakalli, M. ; Pham, Tuan D. ; Lam, K.M. ; Yan, Heng-Chao
Author_Institution :
Dept. of CSE, Marmara Univ., Marmara, Turkey
Abstract :
This paper presents a segmentation methodology of abdominal axial CT images. The aim of the study is to determine the location of mesenteric area from the axial images so the organs enclosed within can be localized precisely for diagnostic purposes. The challenge confronted here is that there is no a certain deterministic shape of abdominal organs. The methodology implemented here utilizes a curvelets stage followed by morphological image processing to achieve a contour emphasized segmentation from the gestalts of surrounding organs. This paper gives a detailed analysis of approach taken with the problems faced and a brief comparison wrt to other wavelet approaches.
Keywords :
biological organs; computerised tomography; curvelet transforms; edge detection; image segmentation; medical image processing; abdominal CT images; contour emphasized segmentation; curvelet-based morphological segmentation; mesenteric area; morphological image processing; wavelet approaches; Computed tomography; Dictionaries; Image edge detection; Image segmentation; Muscles; Shape; Transforms; abdominal image segmentation; connected-components labeling; curvelets; edge and contour detection; non-maximal suppression; wavelets;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
DOI :
10.1109/EMBC.2014.6944882