Title :
A Knowledge-Driven Segmentation Method for Ribs in Bone Scintigraphy Using MRF Model
Author :
Lei Zhou ; Yu Qiao ; Jie Yang
Author_Institution :
Sch. of Electron., Inf. & Electr. Eng., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Bone scintigraphy is a useful tool in diagnosing bone diseases and accurate segmentation of ribs in bones can data-sets is an essential step for accurate diagnosis. It´s a challenging task to demonstrate accurate results due to poor image quality and much extra priority should be introduced for performance improvement. To complete this task, we propose a new Markov random Field (MRF) based framework for automatic segmentation in this paper. In particularly, a series of constraints that force the coarse result of Segmentation to have smooth boundary and connected region are defined. In MRF model, segmentation problem is formed as a discrete labeling problem, so how to unify various constraints into the first-order and secondorderclique potentials of energy function is another challenge which is also studied in the paper. Our main contribution can be summarized as, 1 A framework (GSCSP-B) which is the first detailed method using MRF for segmenting ribs in Bone-Scan image is proposed.2 As to the implementation issue, a method for generating seeds in graph-cut automatically is developed for better user experience.3 Propose a series of constraints, especially the geodesic distance and boundary smoothness constraints and the method for incorporating them into MRF model is presented as well.
Keywords :
Markov processes; bone; differential geometry; diseases; graph theory; image segmentation; medical image processing; radioisotope imaging; GSCSP-B; MRF based framework; MRF model; Markov random field based framework; bone disease diagnosis; bone scintigraphy; bone-scan image; boundary smoothness constraints; discrete labeling problem; energy function; first-order clique potential; geodesic distance; graph-cut; knowledge-driven segmentation method; ribs segmentation; second order clique potential; Bones; Computational modeling; Image color analysis; Image segmentation; Labeling; Ribs; Shape; Bone scintigraphy image; Geodesic distance priority; Graph-cut; Markov Random Field; ribs Segmentation;
Conference_Titel :
Internet Computing for Engineering and Science (ICICSE), 2013 Seventh International Conference on
Conference_Location :
Shanghai
DOI :
10.1109/ICICSE.2013.29