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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Awad, J. Abdel-Galil, T.K. Salama, M.M.A. Tizhoosh, H. Fenster, A. Rizkalla, K. Downey, D.B. |
| Copyright Year | 2003 |
| Description | Author affiliation: Waterloo Univ., Ont., Canada (Awad, J.; Abdel-Galil, T.K.; Salama, M.M.A.; Tizhoosh, H.) |
| Abstract | Prostate cancer is one of the leading causes of cancer death in men. Early detection of prostate cancer is very essential for the success of the treatment. Ultrasound B-mode images is the standard mean for imaging the prostate. The manual analysis of the ultrasound images consumes much time and effort. It is necessary to develop an automated algorithm to analyze the ultrasound images. The first important step in detecting the cancer is to detect the boundary of the prostate itself and to extract it from the image for further analysis. In this paper a multistage algorithm for prostate boundary detection is proposed. In the first stage, the proposed algorithm starts with enhancing the contrast of the image by sticks technique followed by smoothing the image by gauss kernel. In the second stage, scanning the image and applying knowledge base rules to find a seed point inside the prostate is implemented. This seed point is used to remove the false edges. Then by using a morphological opening algorithm, the remaining false edges can be removed. The final step is to use the seed point to scan the image in radial directions to find the prostate' s boundary. |
| Starting Page | 1199 |
| Ending Page | 1202 |
| File Size | 329611 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780377818 |
| ISSN | 08407789 |
| DOI | 10.1109/CCECE.2003.1226113 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-05-04 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ultrasonic imaging Image segmentation Image edge detection Cancer detection Prostate cancer Image analysis Biomedical imaging Medical diagnostic imaging Artificial neural networks Speckle |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Hardware and Architecture |
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