mlsanityData to 7 Oct 2026

Semantic Segmentation and Object Detection Towards Instance Segmentation: Breast Tumor Identification

arXiv 2108.03287 ↗First posted 6 Aug 2021cs.AI cs.CVcited by 0

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Abstract (arXiv)

Breast cancer is one of the factors that cause the increase of mortality of women. The most widely used method for diagnosing this geological disease i.e. breast cancer is the ultrasound scan. Several key features such as the smoothness and the texture of the tumor captured through ultrasound scans encode the abnormality of the breast tumors (malignant from benign). However, ultrasound scans are often noisy and include irrelevant parts of the breast that may bias the segmentation of eventual tumors. In this paper, we are going to extract the region of interest ( i.e, bounding boxes of the tumors) and feed-forward them to one semantic segmentation encoder-decoder structure based on its classification (i.e, malignant or benign). the whole process aims to build an instance-based segmenter from a semantic segmenter and an object detector.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 32 of its 43 references that are in the map. First posted on arXiv 6 Aug 2021.

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32 of 43 references.

References · 32

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20 more
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