@MASTERSTHESIS\{IMM2012-06438, author = "A. M. Sirghie", title = "Abdominal fat segmentation using graph cut methods", year = "2012", school = "Technical University of Denmark, {DTU} Informatics, {E-}mail: reception@imm.dtu.dk", address = "Asmussens Alle, Building 305, {DK-}2800 Kgs. Lyngby, Denmark", type = "", note = "{DTU} supervisors: Rasmus Larsen, Professor, rl@imm.dtu.dk, {DTU} Informatics, Knut Conradsen, Professor, kc@imm.dtu.dk, {DTU} Informatics.", url = "http://www.imm.dtu.dk/English.aspxTo", abstract = "This thesis presents methods for quantifying the subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) volume from {3D} {DIXON} {MRI}. The test data used was acquired as follow up to a study on puberty in Danish children conducted by Copenhagen Department of Growth and Reproduction. Quantifying the {SAT} volume is performed by sequentially detecting the abdomen and {SAT} interior boundaries using a graph-cut based approach. A {3D} weighted graph is constructed in which nodes represent voxels and the edge weights are obtained using a gradient based approach. Finding a surface in the {3D} volume is equivalent to finding the minimum cut in the constructed graph. A special attention is dedicated to investigating the importance of adding ’in-slice’ and ’between-slices’ edge constraints in finding the sought surface. {VAT} estimation is conducted using information from both fat and water images. First a clustering is performed on the fat image, followed by a thresholding of the fat ratio image obtained from the fat and water images. A visual inspection of the {SAT} and {VAT} segmentation results is performed." }