Journal Article

·2017

Meniscus segmentation and tear detection in the knee MR images by fuzzy c-means method

Ahmet Saygılı , Songül Albayrak YTU

Abstract

Computer-assisted diagnosis (CAD) studies on medical images have gained momentum recently. The studies in this area facilitates the work of medical specialists and reduces the time cost. In this study, meniscus segmentation and meniscus tears were performed on 10 different knee MR images in the 3-D DESS standard obtained on the sagittal plane. The morphological operations used in image processing are utilized in the preprocessing stage for segmentation and tear detection. The fuzzy c-means (FCM) method was used to segment the knee joint meniscus tissues and to detect tears. It has been noted that the MR images selected from the meniscus tears differ from each other according to their structures. The next phase of this study will be automatically classified the meniscus according to the types of tears.

Keywords

Meniscus Segmentation Artificial intelligence Tears Computer science Preprocessor Sagittal plane Computer vision Image segmentation Knee Joint Fuzzy logic Biomedical engineering Medicine Radiology Physics Surgery Optics

Subject Areas

Osteoarthritis Treatment and Mechanisms ·Rheumatology ·Health Sciences
Lower Extremity Biomechanics and Pathologies ·Biomedical Engineering ·Physical Sciences
Knee injuries and reconstruction techniques ·Surgery ·Health Sciences

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