| Paper: | WA-P8.5 |
| Session: | Biomedical Imaging IV: Segmentation and Quantitative Analysis |
| Time: | Wednesday, September 19, 09:50 - 12:30 |
| Presentation: |
Poster
|
| Title: |
SEGMENTATION OF MEDICAL ULTRASOUND IMAGES USING ACTIVE CONTOURS |
| Authors: |
Oleg Michailovich; University of Waterloo | | |
| | Allen Tannenbaum; Georgia Institute of Technology | | |
| Abstract: |
Segmentation of medical ultrasound images (e.g., for the purpose of surgical or radiotherapy planning) is known to be a difficult task due to the relatively low resolution and reduced contrast of the images, as well as due to the discontinuity and uncertainty of segmentation boundaries caused by speckle noise. Under such conditions, useful segmentation results seem to be only achievable by means of relatively complex algorithms, which are usually computationally involved and/or require a prior learning. In this paper, a different approach to the problem of segmentation of medical ultrasound images is proposed. In particular, we propose to preprocess the images before they are subjected to a segmentation procedure. The proposed preprocessing modifies the images (without affecting their anatomic contents) so that the resulting images can be effectively segmented by relatively simple and computationally efficient means. The performance of the proposed method is tested in a series of both in silico and in vivo experiments. |
