Automatic Detection of Microcalcifications in ROI Images Based on PFCM and ANN
| Autor: | B. Ojeda-Magaña, J. M. Barrón-Adame, Alexis Marcano-Cedeño, A. Vega-Corona, J. Quintanilla-Dominguez, Diego Andina |
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| Rok vydání: | 2013 |
| Předmět: |
General Computer Science
Artificial neural network Pixel business.industry Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Artificial neural network model Pattern recognition Fuzzy logic Radiology Nuclear Medicine and imaging Artificial intelligence business Cluster analysis |
| Zdroj: | International Journal of Intelligent Computing in Medical Sciences & Image Processing. 5:161-174 |
| ISSN: | 2326-0068 1931-308X |
| Popis: | This paper presents a novel method for the automatic detection of microcalcifications in regions of interest images. Automatic detection method is implemented by feature extraction and sub-segmentation steps. The feature extraction step is improved using a top-hat transform such that microcalcifications can be highlighted. In a second step a sub-segmentation method based on the possibilistic fuzzy c-means clustering algorithm is applied in order to segment the images and as a way to identify the atypical pixels inside the regions of interest as the pixels representing microcalcifications. Once the pixels representing these objects have been identified, an artificial neural network model is used to learn the relations between atypical pixels and microcalcifications, such that the model can be used for aid diagnosis, and a medical could determine if these regions of interest are benign or malignant. So, as the results show, the proposed approach is a good alternative for the detection of suspicious regions,... |
| Databáze: | OpenAIRE |
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