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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lingley-Papadopoulos, C.A. Loew, M.H. Zara, J.M. |
| Copyright Year | 2007 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., George Washington Univ., DC (Lingley-Papadopoulos, C.A.; Loew, M.H.; Zara, J.M.) |
| Abstract | The lining of the bladder is comprised of well defined layers that are clearly visible in optical coherence tomography (OCT) images of healthy bladder tissue. These layers are disturbed when cancerous cells are present. Consequently, recognition and classification of the layers of the bladder is very important in recognizing and staging bladder cancer. We present an algorithm that uses texture analysis, the k-means clustering algorithm, and edge detection software to segment OCT images of the lining of the bladder. We visually segmented 101 OCT images of bladder tissue, ran our algorithm on the images, and compared the results. The segmentation matched 59% of the time, matched reasonably well, with clear sources of error 29% of the time, and was incorrect 12% of the time. The combination of this algorithm with future texture analysis of the segmented layers will provide the tools required to perform a real-time optical biopsy using OCT |
| Starting Page | 1276 |
| Ending Page | 1279 |
| File Size | 276650 |
| Page Count | 4 |
| File Format | |
| ISBN | 1424406714 |
| DOI | 10.1109/ISBI.2007.357092 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-04-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Biomedical optical imaging Biopsy Bladder Image segmentation Clustering algorithms Software algorithms Image texture analysis Algorithm design and analysis Tomography Cancer |
| Content Type | Text |
| Resource Type | Article |
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