Title :
A deformable model for image segmentation in noisy medical images
Author :
Valverde, F.L. ; Guil, N. ; Munoz, J. ; Li, Q. ; Aoyama, M. ; Doi, K.
Author_Institution :
Dept. of Comput. Sci., Malaga Univ., Spain
fDate :
6/23/1905 12:00:00 AM
Abstract :
Deformable-model-based segmentation techniques can overcome some limitations of the traditional image processing techniques. Currently developed deformable models can cope with gaps and another irregularities in object boundaries. However, they present problems in noisy images. Our approach is able to segment objects in noisy images by defining a new energy function associated with image noise and avoiding the tendency of contour points to bunch up. The model is validated for vessel segmentation on mammograms
Keywords :
edge detection; image segmentation; mammography; medical image processing; contour points; deformable model; energy function; image noise; image processing; image segmentation; mammograms; noisy medical images; vessel segmentation; Biomedical imaging; Computer architecture; Computer science; Deformable models; Dynamic programming; Image reconstruction; Image segmentation; Laboratories; Shape; Solid modeling;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.958056
