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Conference Papers Year : 2022

Breast Cancer Detection from Histopathology Images Based on YOLOv5

Abstract

In biomedicine, cells nuclei detection is a leading topic research and one of the most challenging. Histopathological analysis represents the cells of the tissue sample that provide a set of essential information for detection and characterization of the cancer. Deep learning (DL) has recently demonstrated promising performance in breast cancer diagnosis, thus in this paper, we present a cells detection algorithm, based on the well-knownYOLOv5 DL model as the backbone network. The proposed algorithm is applied on a public dataset of hematoxylin and eosin (H&E) stained tissue images for evaluation.
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Dates and versions

hal-03958399 , version 1 (26-01-2023)

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Wafaa Rajaa Drioua, Nacéra Benamrane, Lakhdar Saïs. Breast Cancer Detection from Histopathology Images Based on YOLOv5. 7th International Conference on Frontiers of Signal Processing (ICFSP), Sep 2022, Paris, France. ⟨10.1109/ICFSP55781⟩. ⟨hal-03958399⟩
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