Automated Detection of Tumors in Mammograms Using Two Segments for Classification

Abstract

Abstract.A spread pattern of a tumor in medical images is an important factor for classification of the tumor. The spread pattern is generally not considered when we use only one segment for classification. In order to include the spread pattern for tumor analysis, we propose an approach for classification of tumors in mammograms using two segments for a mass. The proposed approach is performed in two stages. In the first stage, the system separates segments of the image that may correspond to tumors using a combination of morphological operations and a region growing technique. In the second stage, segmented regions are classified as normal, benign, or malignant tissues based on different measurements. The measurements pertain to shape, intensity variation around the mass, as well as the spread pattern. Experimental results with mammogram images of the MIAS database show reasonable improvements in correct detection of possible tumors, compared to other approaches.

Breast mass detection in digital mammography based on anchor-free architecture

“…Although the traditional BMass detection method has certain limitations, it has made some progress [15][16][17][18]. For example, based on threshold segmentation [14], region growing [19,20], watershed [20,21], edge detection [22,23]. Specifically and trimming, the detection performance of the small BMass is improved [33].…”

A New CAD System for Breast Microcalcifications Diagnosis

“…This category includes regions based approaches, such as regions growing algorithm [33,53,71], watershed algorithm [32] and Split and Merge algorithm [13]. Some other approaches are based on the edge detection of mammogram components [5,10,21,25,28,34,37] We also find, in this category, clustering based approaches.…”

Decisions Fusion Strategy: Towards Hybrid Cluster Ensemble

“…However, there are some approaches which are quite relevant to our work have demonstrated some interesting facts. In [17], Mahmoud proposed the approach for the classification of tumors (masses) in mammograms using two segments approach. In the first stage, he extracted mammography features by using a combination of morphological operations and a region growing technique.…”