NDLI: Fully Automatic Segmentation of Abdominal Organs from CT Images Using Fast Marching Methods

Content Provider	IEEE Xplore Digital Library
Author	Campadelli, P. Casiraghi, E. Pratissoli, S.
Copyright Year	2008
Description	Author affiliation: Dipt. di Sci. dell'Inf., Univ. degli Studi di Milano, Milan (Campadelli, P.; Casiraghi, E.; Pratissoli, S.)
Abstract	Computed tomography (CT) images are becoming an invaluable mean for abdominal organ investigation. In the field of medical image processing, some of the current interests are the automatic diagnosis of liver, spleen, and kidney pathologies and the 3D volume rendering of the abdominal organs. The first and fundamental step in all these studies is the automatic organs segmentation, that is still an open problem. In this paper we propose a fully automatic gray level based segmentation framework that employs a fast marching technique; the proposed segmentation scheme is general, and employs only established and not critical anatomical knowledge. For this reason, it can be easily adapted to separately segment different abdominal organs, by overcoming problems due to the high inter and intra patient gray level and shape variabilities; the extracted volumes are then combined to achieve robust results. The system performance has been evaluated on the data of 40 patients, by comparing the automatically detected organ volumes to the organ boundaries manually traced by three experts. The good quality of the achieved results is proved by the fact that they are comparable to the inter and intra personal variability of the manual segmentation produced by experts.
Starting Page	554
Ending Page	559
File Size	916792
Page Count	6
File Format	PDF
ISBN	9780769531656
ISSN	10637125
DOI	10.1109/CBMS.2008.9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-17
Publisher Place	Finland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Abdomen Computed tomography Biomedical image processing Liver Pathology Rendering (computer graphics) Shape Data mining Robustness fast marching Abdominal Organ Segmentation CT images diffusion filter
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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