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Carreras Cruz, María Victoria
Circumscribed Mass Detection in Digital Mammograms
Mass Segmentation in Digital Mammograms
2006
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Carreras Cruz, María Victoria
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Rayon Vilella, Patricia
The incidence of breast cancer in women has increased significantly in recent years. This paper proposes a computer aided diagnostic system for mammographic circumscribed mass detection. The propose method can distinguish between tumours and healthy tissue among various parenchymal tissue patterns. In the first stage the preprocessing and features extraction of the image is done. In this way image segmentation, filtering, contrast improvement and gray level thresholding techniques are applied for enhancing the whole image, and then the features are extracted from the resultant image. In the second part a k-means clustering algorithm is applied. The evaluation of the propose methodology is carried out on Mammography Image Analysis Society (MIAS) dataset.
2015
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Carreras Cruz, María Victoria
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Martinez-Villaseñor, Lourdes
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Rosas-Pérez, Kevin Nataniel
Digital mammograms are among the most difficult medical images to read, because of the differences in the types of tissues and their low contrasts. This paper proposes a computer aided diagnostic system for mammographic mass detection that can distinguish between tumorous and healthy tissue among various parenchymal tissue patterns. This method consists in extraction of regions of interest, noise elimination, global contrast improvement, combined segmentation, and rule-based classification. The evaluation of the proposed methodology is carried out on Mammography Image Analysis Society (MIAS) dataset. The achieved results increased the detection accuracy of the lesions and reduced the number of false diagnoses of mammograms.