title: Automated segmentation of necrotic femoral head from 3D MR data.
abstract: Segmentation of diseased organs is an important topic in computer assisted medical image analysis. In particular, automatic segmentation of necrotic femoral head is of importance for various corresponding clinical tasks including visualization, quantitative assessment, early diagnosis and adequate management of patients suffering from avascular necrosis of the femoral head (ANFH). Early diagnosis and treatment of ANFH is crucial since the disease occurs in relatively young individuals with an average age of 20-50, and since treatment options for more advanced disease are frequently unsuccessful. The present paper describes several new techniques and software for automatic segmentation of necrotic femoral head based on clinically obtained multi-slice T1-weighted MR data. In vivo MR data sets of 50 actual patients are used in the study. An automatic method built up to manage the segmentation task according to image intensity of bone tissues, shape of the femoral head, and other characters. The processing scheme consisted of the following five steps. (1) Rough segmentation of non-necrotic lesions of the femur by applying a 3D gray morphological operation and a 3D region growing technique. (2) Fitting a 3D ellipse to the femoral head by a new approach utilizing the constraint of the shape of the femur, and employing a principle component analysis and a simulated annealing technique. (3) Estimating the femoral neck location, and also femoral head axis by integrating anatomical information of the femur and boundary of estimated 3D ellipse. (4) Removal of non-bony tissues around the femoral neck and femoral head ligament by utilizing the estimated femoral neck axis. (5) Classification of necrotic lesions inside the estimated femoral head by a k-means technique. The above method was implemented in a Microsoft Windows software package. The feasibility of this method was tested on the data sets of 50 clinical cases (3000 MR images).
authors.affiliation: Department of Electrical and Computer Engineering, Faculty of Engineering, Center of Excellence for Control and Intelligent Processing, University of Tehran, Tehran 14395/515, Iran. zoroofi@ut.ac.ir
authors.forename: Reza A
authors.initials: RA
authors.lastname: Zoroofi
authors.forename: Yoshinobu
authors.initials: Y
authors.lastname: Sato
authors.forename: Takashi
authors.initials: T
authors.lastname: Nishii
authors.forename: Nobuhiko
authors.initials: N
authors.lastname: Sugano
authors.forename: Hideki
authors.initials: H
authors.lastname: Yoshikawa
authors.forename: Shinichi
authors.initials: S
authors.lastname: Tamura
mesh_terms: D001331:Automation; D005271:Femur Head Necrosis / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007564:Japan; D008279:Magnetic Resonance Imaging / Q000379:methods*; D012984:Software