3D imaging in medicine
Graphical Models and Image Processing
Scale-based fuzzy connected image segmentation: theory, algorithms, and validation
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Three-dimensional visualization in medicine and biology
Handbook of medical imaging
Multiseeded Segmentation Using Fuzzy Connectedness
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Models in Medical Image Analysis
Deformable Models in Medical Image Analysis
Gradient Vector Flow Fast Geometric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We have developed intelligent software tools for handling the uncertainty in delineating the boundaries of complex structures when segmenting regions of interest (ROIs) in medical images. The focus is on efficiently delineating the boundary of complex 3D organ structures, enabling accurate measurement of their structural and physiologic properties. We employ intensity based thresholding algorithms for interactive and semi-automated analysis. We also explore fuzzy-connectedness concepts in order to deal with the uncertainty in identifying organ surrounding tissue and fully automate the segmentation process. We apply the proposed tools to 3D single-photon emission computed tomography (SPECT) images visualising gastric accommodation and emptying and compare their performance to that of the manual segmentation performed by a human expert. We show that the proposed tools achieve highly accurate delineation of the complex three-dimensional gastric boundaries shown in 3D SPECT images. We also demonstrate their ability to obtain accurate volume calculations based on the segmentation procedure, in order to quantitatively assess organ functional properties such as measuring the gastric mass variation.