Breast Histopathology Image Retrieval by Attention-based Adversarially Regularized Variational Graph Autoencoder with Contrastive Learning-Based Feature Extraction

arXiv:2405.04211v1 Announce Type: new
Abstract: Breast cancer is a significant global health concern, particularly for women. Early detection and appropriate treatment are crucial in mitigating its impact, with histopathology examinations playing a vital role in swift diagnosis. However, these examinations often require a substantial workforce and experienced medical experts for proper recognition and cancer grading. Automated image retrieval systems have the potential to assist pathologists in identifying cancerous tissues, thereby accelerating the diagnostic process. Nevertheless, due to considerable variability among …

abstract arxiv attention autoencoder cancer cs.cv detection diagnosis extraction feature feature extraction global global health graph health however image impact playing retrieval role swift treatment type vital women