Computer aided system for segmentation and visualization of microcalcifications in digital mammograms
| Autor: | Branimir Reljin, Irini Reljin, Zorica Milosević, Tomislav Stojić |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Pathology
medicine.medical_specialty Histology Computer science Breast Neoplasms Mathematical morphology Sensitivity and Specificity 030218 nuclear medicine & medical imaging Pathology and Forensic Medicine 03 medical and health sciences Digital image 0302 clinical medicine medicine Humans Mammography Segmentation Computer vision lcsh:QH573-671 medicine.diagnostic_test lcsh:Cytology business.industry Calcinosis Reproducibility of Results General Medicine Visualization Radiographic Image Enhancement 030220 oncology & carcinogenesis Computer-aided Radiographic Image Interpretation Computer-Assisted Female Artificial intelligence Microcalcification medicine.symptom business Algorithms |
| Zdroj: | Folia Histochemica et Cytobiologica, Vol 47, Iss 3, Pp 525-532 (2010) |
| ISSN: | 1897-5631 0239-8508 |
| DOI: | 10.2478/v10042-009-0076-1 |
| Popis: | Two methods for segmentation and visualization of microcalcifications in digital or digitized mammograms are described. First method is based on modern mathematical morphology, while the second one uses the multifractal approach. In the first method, by using an appropriate combination of some morphological operations, high local contrast enhancement, followed by significant suppression of background tissue, irrespective of its radiology density, is obtained. By iterative procedure, this method highly emphasizes only small bright details, possible microcalcifications. In a multifractal approach, from initial mammogram image, a corresponding multifractal "images" are created, from which a radiologist has a freedom to change the level of segmentation. An appropriate user friendly computer aided visualization (CAV) system with embedded two methods is realized. The interactive approach enables the physician to control the level and the quality of segmentation. Suggested methods were tested through mammograms from MIAS database as a gold standard, and from clinical praxis, using digitized films and digital images from full field digital mammograph. |
| Databáze: | OpenAIRE |
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