Bone & bone lesion segmentation in SPECT/CT with the modified Robust Fuzzy C-means

This is an implementation of my paper:

Chen, Junyu, et al. "Incorporating CT prior information in the robust fuzzy C-means algorithm for QSPECT image segmentation." Proceedings Volume 10949, SPIE Medical Imaging 2019: Image Processing.

This segmentation method was based the Robust Fuzzy C-means algorithm by Dr. Dzung L.Pham, with the incorporation of prior knowledge from the CT clustering.

Preprocess Images:

Crop a small region of interest in both SPECT and CT image.

Objective Function:

Sample Results:

Red contours in the images represent segmented bone regions and green contours indicate lesion regions. The segmentation result in image (a) was obtained with β = 0.0005 and γ = 0. The segmentation results in images (b), (c), and (d) were obtained with β = 0.0005 and γ = 0.005, 0.01, and 0.05, respectively.

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