Fast microcalcification detection on digital breast tomosynthesis datasets
| Autor: | Razvan Iordache, Sylvain Bernard, Serge Muller, Gero L. Peters |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
medicine.diagnostic_test
business.industry Computation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image segmentation Thresholding Tomosynthesis Contrast-to-noise ratio medicine Mammography Computer vision Microcalcification Artificial intelligence Noise (video) medicine.symptom business Mathematics |
| Zdroj: | Medical Imaging: Computer-Aided Diagnosis |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.709987 |
| Popis: | In this paper, we present a fast method for microcalcification detection in Digital Breast Tomosynthesis. Instead of applying the straight-forward reconstruction/filtering/thresholding approach, the filtering is performed on projections before simple back-projection reconstruction. This leads to a reduced computation time since the number of projections is generally much smaller than the number of slices. For an average breast thickness and a typical number of projections, the number of operations is reduced by a factor in the range of 2 to 4. At the same time, the approach yields a negligible decrease of the contrast to noise ratio in the reconstructed slices. Image segmentation results are presented and compared to the previous method as visual performance assessment. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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