TY  - JOUR
T1  - Automatic Segmentation of Femoral Cartilage in Knee MR Images using Multi-atlas-based Locally-weighted Voting
AU  - Kim, Hyeun A 
AU  - Kim, Hyeonjin 
AU  - Lee, Han Sang 
AU  - Hong, Helen 
JO  - Journal of KIISE, JOK
PY  - 2016
DA  - 2016/1/14
DO  - 
KW  - knee MRI
KW  - femoral cartilage segmentation
KW  - femur segmentation
KW  - locally-weighted voting
KW  - multi-atlas segmentation
AB  - In this paper, we propose an automated segmentation method of femoral cartilage in knee MR images using multi-atlas-based locally-weighted voting. The proposed method involves two steps. First, to utilize the shape information to show that the femoral cartilage is attached to a femur, the femur is segmented via volume and object-based locally-weighted voting and narrow-band region growing. Second, the object-based affine transformation of the femur is applied to the registration of femoral cartilage, and the femoral cartilage is segmented via multi-atlas shape-based locally-weighted voting. To evaluate the performance of the proposed method, we compared the segmentation results of majority voting method, intensity-based locally-weighted voting method, and the proposed method with manual segmentation results defined by expert. In our experimental results, the newly proposed method avoids a leakage into the neighboring regions having similar intensity of femoral cartilage, and shows improved segmentation accuracy.