Anisotropic Curvature Motion for Structure Enhancing Smoothing of 3D MR Angiography Data
Journal of Mathematical Imaging and Vision
Automatic liver segmentation from abdominal CT scans
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Liver Segmentation from CT Scans: A Survey
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Hybrid image segmentation using watersheds and fast region merging
IEEE Transactions on Image Processing
Graph-Cut Energy Minimization for Object Extraction in MRCP Medical Images
Journal of Medical Systems
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This work presents a method for liver isolation in magnetic resonance imaging (MRI) abdomen images. It is based on a priori statistical information about the shape of the liver obtained from a training set using the segmentation approach. Morphological watershed algorithm is used as a key technique as it is a simple and intuitive method, producing a complete division of the image in separated regions even if the contrast is poor, and it is fast, with possibility for parallel implementation. To overcome the over-segmentation problem of the watershed process, image preprocessing and post-processing are applied. Morphological smoothing, Gaussian smoothing, intensity thresholding, gradient computation and gradient thresholding are proposed for preprocessing with morphological and graph based region adjacent list constructed for region merging. A new integrated region similarity function is also defined for region merging control. The proposed method produces good isolation of liver in axial MRI images of the abdomen, as is shown in this paper.