Knee cartilage segmentation using active shape models and contrast enhancement from magnetic resonance images

Germán González; Boris Escalante-Ramírez

doi:10.1117/12.2035529

19 November 2013 Knee cartilage segmentation using active shape models and contrast enhancement from magnetic resonance images

Germán González, Boris Escalante-Ramírez

Author Affiliations +

Proceedings Volume 8922, IX International Seminar on Medical Information Processing and Analysis; 892213 (2013) https://doi.org/10.1117/12.2035529
Event: IX International Seminar on Medical Information Processing and Analysis, 2013, Mexico City, Mexico

Abstract

In this paper, we propose to take advantage from the contrast characteristics of our magnetic resonance images in order to improve the performance of Active Shape Models (ASM) applied to knee cartilage segmentation, since ASM depends directly of the contrast between objects. We realize an image fusion-based contrast enhancement between slices from magnetic resonance image volumes, then, we test the ASM algorithm with contrast enhancement images and compare results with ASM without contrast enhancement. The results are very clear, the ASM with contrast enhancement has a better performance and consistence, and we validate this results using Dice coefficient and Hausdorff distance. Moreover, we validate contrast enhancement to assure that really we are improving the contrast image.

Citation Download Citation

Germán González and Boris Escalante-Ramírez "Knee cartilage segmentation using active shape models and contrast enhancement from magnetic resonance images", Proc. SPIE 8922, IX International Seminar on Medical Information Processing and Analysis, 892213 (19 November 2013); https://doi.org/10.1117/12.2035529

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