{"doi":"10.34133/bmef.0048","title":"Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling","abstract":"Objective and Impact Statement: Human epidermal growth factor receptor 2 (HER2) is a critical protein in cancer cell growth that signifies the aggressiveness of breast cancer (BC) and helps predict its prognosis. Here, we introduce a deep learning-based approach utilizing pyramid sampling for the automated classification of HER2 status in immunohistochemically (IHC) stained BC tissue images. Introduction: Accurate assessment of IHC-stained tissue slides for HER2 expression levels is essential for both treatment guidance and understanding of cancer mechanisms. Nevertheless, the traditional workflow of manual examination by board-certified pathologists encounters challenges, including inter- and intra-observer inconsistency and extended turnaround times. Methods: Our deep learning-based method analyzes morphological features at various spatial scales, efficiently managing the computational load and facilitating a detailed examination of cellular and larger-scale tissue-level details. Results: This approach addresses the tissue heterogeneity of HER2 expression by providing a comprehensive view, leading to a blind testing classification accuracy of 84.70%, on a dataset of 523 core images from tissue microarrays. Conclusion: This automated system, proving reliable as an adjunct pathology tool, has the potential to enhance diagnostic precision and evaluation speed, and might substantially impact cancer treatment planning.","journal":"BME Frontiers","year":2024,"id":420851,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":32,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9586,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":854652,"name":"Xilin Yang","orcid":"0000-0002-6954-9662","position":1,"is_corresponding":false},{"id":854645,"name":"Bijie Bai","orcid":"0000-0002-4744-996X","position":2,"is_corresponding":false},{"id":1212422,"name":"Yijie Zhang","orcid":"0000-0003-1594-1789","position":3,"is_corresponding":false},{"id":854647,"name":"Yuzhu Li","orcid":"0009-0007-1570-0324","position":4,"is_corresponding":false},{"id":1212423,"name":"Musa Aydın","orcid":"0000-0002-5825-2230","position":5,"is_corresponding":false},{"id":1212934,"name":"Aras Firat Unal","orcid":null,"position":6,"is_corresponding":false},{"id":1212935,"name":"Aditya Gomatam","orcid":null,"position":7,"is_corresponding":false},{"id":1212424,"name":"Zhen Guo","orcid":"0000-0003-4875-5149","position":8,"is_corresponding":false},{"id":1212936,"name":"D Angus","orcid":null,"position":9,"is_corresponding":false},{"id":1212937,"name":"Goren Kolodney","orcid":null,"position":10,"is_corresponding":false},{"id":239094,"name":"Karine Atlan","orcid":null,"position":11,"is_corresponding":false},{"id":1205488,"name":"Tal Keidar Haran","orcid":"0000-0003-1931-706X","position":12,"is_corresponding":false},{"id":430499,"name":"Nir Pillar","orcid":"0000-0003-4979-1440","position":13,"is_corresponding":false},{"id":456451,"name":"Aydogan Özcan","orcid":"0000-0002-0717-683X","position":14,"is_corresponding":false},{"id":1212421,"name":"Şahan Yoruç Selçuk","orcid":"0000-0002-6721-3540","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-19T01:57:31.041511Z","pmid":"39045139","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}