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논문검색

Automatic Segmentation of Femoral Cartilage from MR Image Based on Hough Transform and Adaptive Canny Detection

초록

영어

Medical image segmentation has important significance for thickness estimation of the articular cartilage and joint disease diagnosis. In this study, a novel automatic segmentation method based on Hough transform and edge detection was proposed to divide femoral cartilage in human hip joint from MR images. MR image was interpolated, smoothed and enhanced in preprocessing to improve the image quality. Hough transform was employed to find out the center position of the femoral head and the anatomical constrain of the hip joint was considered to estimate the area of interest (AOI). Furthermore, the rough segmentation range was extracted. To figure out the border of the cartilage, the adaptive thresholding Canny detector was exerted. The detected edges were then labeled and filtered in a custom one by one manner to remove the noise edges and acquire the exact inner and outer edges of the femoral cartilage, according to the properties of the pixel on femoral cartilage edge. Image data between the two edges were finally extracted to achieve the femoral cartilage segmentation. Experiment on 120 MR image slices proved that the method can automatically segment the femoral cartilage fast and accurately.

목차

Abstract
 1. Introduction
 2. Image Preprocessing
 3. Image Segmentation
  3.1. Center Extraction based on the Hough Transform
  3.2. Select Rough Region
  3.3. Accurate Edge Extraction and Segmentation
 4. Experiment
 5. Conclusion
 Acknowledgements
 References

저자정보

  • Yu Cao School of Automation Harbin University of Science and Technology
  • Xia Liu School of Automation Harbin University of Science and Technology
  • Yang Cao School of Automation Harbin University of Science and Technology
  • Yu-nan Liu School of Foreign Languages Harbin University of Science and Technology

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