Electronic Letters on Computer Vision and Image Analysis 8(1):1-14, 2009
Automatic Abdominal Organ Segmentation from CT images
Paola Campadelli∗, Elena Casiraghi∗, Stella Pratissoli∗, Gabriele Lombardi∗
∗ Department of Computer Science, Universitá degli studi di Milano, Via Comelico 39/41, Milan, Italy
Received 26 May 2008; accepted 13 January 2009
In the recent years a great deal of research work has been devoted to the development of semi-automatic
and automatic techniques for the analysis of abdominal CT images. 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 our fully automatic system that employs a hierarchical gray
level based framework to segment heart, bones (i.e. ribs and spine), liver and its blood vessels, kidneys, and
spleen. The overall system has been evaluated on the data of 100 patients, obtaining a good assessment both
by visual inspection by three experts, and by comparing the computed results to the boundaries manually
traced by experts.
Key Words: Abdominal CT images, 3D organs segmentation, histogram analysis, graph cut, α-expansion.
Imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), or positron emis-
sion tomography (PET) are nowadays a standard instrument for diagnosis of abdominal organs pathologies.
Among these techniques, CT images are often preferred by diagnosticians since they have high Signal-to-Noise
ratio and good spatial resolution, thus providing accurate anatomical information about the visualized struc-
tures. These good image qualities, and the advances in the digital image processing techniques, motivate the
great deal of research work aimed at the development of computerized methods for the automatic abdominal
organ analysis and 3D volume rendering. More precisely, some