A Semi-automated Method for the Liver Lesion Extraction From a CT Images Based on Mathematical Morphology

The liver is a common site for the tumors occurrence. Automatic hepatic lesion segmentation is a crucial step for diagnosis and surgery procedure. When computed tomography (CT) scans is used, liver lesions segmentation is a challenging task. In CT images, hepatic lesions located in a liver are generally identified by intensity difference between lesions and liver. In fact, the intensity of the lesions can be lower or higher than that of the liver. In this work, the segmentation is performed in two stages. In the primary stage, the liver structure will be at first extracted from the image using the morphological reconstruction. The second stage is devoted to detect the hepatic lesions by the watershed transform. However, the segmentation procedure; as it is mentioned previously; is a difficult task. In fact, the main problem of liver lesions detection from CT images is related to low contrast between lesions and liver intensities. To solve this problem, a new method developed for the semi-automatic segmentation of hepatic lesions is developed. It   is based on the anatomical information and mathematical morphology tools that are used in the image processing field. The proposed segmentation algorithm is evaluated by comparing our results with the manual segmentation performed by an expert.

Author(s): Belgherbi A. , Hadjidj I. , Bessaid A.

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