Name
Abstract | ||
|---|---|---|
The aim of the presented system is simplification and speedup of the daily pathological examination routine. The system combines telepathology with computer-aided diagnostics algorithms. To the best of our knowledge, this is the first approach proposing such a comprehensive method. Our system is designed to accumulate knowledge through a learning process during diagnostics. Our system targets image acquisition and interpretation stages. The image acquisition subsystem solves various problems related to microscopical slide digitization such as biomedical image registration, data representation, and processing. The in- terpretation subsystem is based on Gabor filter texture features as well as on color features. A support vector machine classifier together with a feature selection is used for computer-aided diagnostics. The system design allows easy adaptation to a wide range of microscopical pathology examinations. The system is easily deployed and scaled. It has a low support cost and can aggregate a wide range of existing hardware. The experimental validation of the system is based on a database of more than three thousand samples. During the experimental evaluation, the system exhibited successful interaction with a pathologist. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.4304/jmm.1.7.40-48 | Journal of Multimedia |
Keywords | DocType | Volume |
multiresolution analysis,index terms— computer-aided diagnostics,microscopical telepatology | Journal | 1 |
Issue | Citations | PageRank |
7 | 1 | 0.37 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Grigory Begelman | 1 | 29 | 3.22 |
| Michael Pechuk | 2 | 20 | 2.11 |
| Ehud Rivlin | 3 | 440 | 82.03 |
| Edmond Sabo | 4 | 7 | 1.94 |