| 講演抄録／キーワード |
| 講演名 |
2009-01-19 15:55
Content-Based Retrieval of Pathological Prostate Images
P. W. Huang・○Cheng-Hsiung Lee（National Chung Hsing Univ.） |
| 抄録 |
（和） |
In this paper, we develop a content-based image retrieval (CBIR) system for histological prostate cancer. In our system, a physician can find prostate images of similar cancer grade from archive by example in terms of visual similarity of different Gleason grading. The Gleason grading system is the widespread method for histological grading of prostate cancer. Two feature extraction methods based on fractal dimension are proposed to analyze variations of intensity and texture complexity in regions of interest. Our experiments are based on a database consisting of 205 prostate pathological images. The performance of retrieval system is evaluated using precision-recall curves. |
| （英） |
In this paper, we develop a content-based image retrieval (CBIR) system for histological prostate cancer. In our system, a physician can find prostate images of similar cancer grade from archive by example in terms of visual similarity of different Gleason grading. The Gleason grading system is the widespread method for histological grading of prostate cancer. Two feature extraction methods based on fractal dimension are proposed to analyze variations of intensity and texture complexity in regions of interest. Our experiments are based on a database consisting of 205 prostate pathological images. The performance of retrieval system is evaluated using precision-recall curves. |
| キーワード |
（和） |
Prostate cancer / Gleason grading / Content-based image retrieval (CBIR) / Fractal dimension / / / / |
| （英） |
Prostate cancer / Gleason grading / Content-based image retrieval (CBIR) / Fractal dimension / / / / |
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