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SEGMENTATION OF MEDICAL IMAGES USING ACTIVE CONTOURS AND GRADIENT VECTOR FLOW B.Hemakumar

SEGMENTATION OF MEDICAL IMAGES USING ACTIVE CONTOURS AND GRADIENT VECTOR FLOW B.Hemakumar M.Tech student, Biomedical signal processing and Instrumentation, Dept. of Electronics and Instrumentation, SASTRA deemed university, Tanjore, India. OUTLINE OF PRESENTATION. Active contours

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SEGMENTATION OF MEDICAL IMAGES USING ACTIVE CONTOURS AND GRADIENT VECTOR FLOW B.Hemakumar

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  1. SEGMENTATION OF MEDICAL IMAGES USING ACTIVE CONTOURS AND GRADIENT VECTOR FLOW B.Hemakumar M.Tech student, Biomedical signal processing and Instrumentation, Dept. of Electronics and Instrumentation, SASTRA deemed university, Tanjore, India.

  2. OUTLINE OF PRESENTATION • Active contours • Introduction • Applications • Problems – conventional snakes • Existing Methods • GVF Method • GVF snake • Results • Conclusion

  3. ACTIVE CONTOURS Active contours -- or snakes -- are computer-generated curves that move within images to find object boundaries Curves defined within an image domain that can move under the influence of internal forces within the curve itself and external forces derived from the image data

  4. ACTIVE CONTOURS contd… • Basic idea – MODELLING • MODEL evaluated based on INT & EXT properties • MODEL can move, shrink and expand • 3 Forces govern the motion of SNAKE • Int. forces • Ext. forces • Image forces

  5. APPLICATIONS • CARDIAC DISORDERS • CC – GOLD STANDARD • Role of Active contour • PROSTATE CANCER • Biopsy • Role of Active contours

  6. PROBLEMS WITH CONVENTIONAL SNAKES • Snakes cannot move toward objects that are too far away • Snakes cannot move into boundary concavities or indentations

  7. EXISTING METHODS • Multiresolution methods have addressed the issue of initialization, but specifying how the snake should move across different resolutions remains problematic • Pressure forces, can push an active contour into boundary concavities, but cannot be too strong or “weak” edges will be overwhelmed • Distance potential forces • Control points • Solenoidal external fields

  8. EXISTING METHODS contd.. Previous efforts to solve these problems have not been completely successful, and have often created new problems along with the proposed solutions.

  9. GVF METHOD We present a new class of external forces for active contour models that addresses the problems listed previously. The GVF forces are used to drive the snake, modeled as a physical object having a resistance to both stretching and bending, toward the boundaries of the object. The GVF forces are calculated by applying generalized diffusion equations to both components of the gradient of an image edge map.

  10. GVF METHOD contd.. Because the GVF forces are derived from a diffusion operation, they tend to extend very far away from the object. This extends the "capture range" so that snakes can find objects that are quite far away from the snake's initial position. This same diffusion creates forces which can pull active contours into concave regions.

  11. RESULTS We have developed a graphical user interface (GUI) using MATLAB 6.1 MRI and ultrasound Imaging were done at Govt. General hospital, Karaikal. We have tested our GVF snake on many types of objects, from simple shapes to magnetic resonance images of the heart and brain, renal and prostate cancer ultrasound images

  12. RESULTS contd.. (GUI)

  13. RESULTS contd.. MRI images of Heart Ultrasound images of the prostate cancer

  14. CONCLUSION The GVF snake is a new approach to active contours and surfaces. It focuses on the design of the external force first, and the implementation of the snake second. The computations are straightforward, i.e., the diffusion equations are simple to calculate, and the result is always better than the traditional snake.

  15. KEY REFERENCES • Chenyang Xu and Jerry L. Prince, “Gradient Vector Flow: A New External Force for Snakes”, IEEE Proc. Conf. on Comp. Vis. Patt. Recog. (CVPR'97) • http://iacl.ece.jhu.edu/projects/gvf/ • 3. P. Abolmaesumi, “SEGMENTATION OF PROSTATE CONTOURS FROM ULTRASOUND IMAGES”, IEEE Trans. Med. Imag., vol. 22, no. 4, pp. • 539–551, 2003

  16. ACLNOWLEDGEMENT Dr. G. BALACHANDIRAN, M.B.B.S., M.D., D.M.R.D., DNB, M.I.C.R., HEAD OF DEPARTMENT, Dept. of Radiology, Govt. General Hospital, Karaikal.

  17. THANKS FOR YOUR ATTENTION

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