Medical image segmentation by MDP model

Yisu Lu; Wufan Chen

doi:10.1117/12.901999

5 December 2011 Medical image segmentation by MDP model

Yisu Lu, Wufan Chen

Proceedings Volume 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing; 80050T (2011) https://doi.org/10.1117/12.901999
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

MDP (Dirichlet Process Mixtures) model is applied to segment medical images in this paper. Segmentation can been automatically done without initializing segmentation class numbers. The MDP model segmentation algorithm is used to segment natural images and MR (Magnetic Resonance) images in the paper. To demonstrate the accuracy of the MDP model segmentation algorithm, many compared experiments, such as EM (Expectation Maximization) image segmentation algorithm, K-means image segmentation algorithm and MRF (Markov Field) image segmentation algorithm, have been done to segment medical MR images. All the methods are also analyzed quantitatively by using DSC (Dice Similarity Coefficients). The experiments results show that DSC of MDP model segmentation algorithm of all slices exceed 90%, which show that the proposed method is robust and accurate.

Citation Download Citation

Yisu Lu and Wufan Chen "Medical image segmentation by MDP model", Proc. SPIE 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing, 80050T (5 December 2011); https://doi.org/10.1117/12.901999

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