Title :
Detecting and visualizing cartilage thickness without a shape model
Author :
Li, Shengzhe ; Cui, Xuenan ; Yu, Miao ; Kim, Hakil ; Kwack, Kyu-Sung
Author_Institution :
Sch. of Inf. & Commun. Eng., Inha Univ., Incheon, South Korea
Abstract :
This paper proposes a cartilage thickness detection and visualization method that does not utilize a shape model. The proposed method consists of three parts: volume of interest (VOI) initialization, bone segmentation, and cartilage thickness visualization. For VOI initialization, a novel 3D U-shape cuboidal filter is proposed to detect individual bones such as the femur, tibia, and patella, and for bone segmentation, a hybrid level-set method is adopted. Finally, a surface normal based approach is presented for measuring and visualizing the cartilage thickness. The advantage of the proposed method compared to other methods is that it does not require a shape model or any training process. The results demonstrate that the proposed method can be used for inspecting cartilage damage and loss.
Keywords :
automatic optical inspection; biomedical MRI; bone; data visualisation; filtering theory; image segmentation; thickness measurement; 3D U-shape cuboidal filter; VOI initialization; bone detection; bone segmentation; cartilage damage inspection; cartilage loss inspection; cartilage thickness detection method; cartilage thickness measurement; cartilage thickness visualization method; hybrid level-set method; osteoarthritis; surface normal based approach; volume of interest initialization; Biomedical imaging; Bones; Image segmentation; Magnetic resonance imaging; Shape; Training; Visualization; OA; bone segmentation; knee cartilage; non-model-based detection;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6377705