{"doi":"10.1038/s41467-024-47065-2","title":"DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology","abstract":"Histopathology plays a critical role in the diagnosis and surgical management of cancer. However, access to histopathology services, especially frozen section pathology during surgery, is limited in resource-constrained settings because preparing slides from resected tissue is time-consuming, labor-intensive, and requires expensive infrastructure. Here, we report a deep-learning-enabled microscope, named DeepDOF-SE, to rapidly scan intact tissue at cellular resolution without the need for physical sectioning. Three key features jointly make DeepDOF-SE practical. First, tissue specimens are stained directly with inexpensive vital fluorescent dyes and optically sectioned with ultra-violet excitation that localizes fluorescent emission to a thin surface layer. Second, a deep-learning algorithm extends the depth-of-field, allowing rapid acquisition of in-focus images from large areas of tissue even when the tissue surface is highly irregular. Finally, a semi-supervised generative adversarial network virtually stains DeepDOF-SE fluorescence images with hematoxylin-and-eosin appearance, facilitating image interpretation by pathologists without significant additional training. We developed the DeepDOF-SE platform using a data-driven approach and validated its performance by imaging surgical resections of suspected oral tumors. Our results show that DeepDOF-SE provides histological information of diagnostic importance, offering a rapid and affordable slide-free histology platform for intraoperative tumor margin assessment and in low-resource settings.","journal":"Nature Communications","year":2024,"id":423693,"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":23,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9529,"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":294092,"name":"Yubo Tang","orcid":"0000-0003-2568-8940","position":1,"is_corresponding":false},{"id":294094,"name":"Jackson B. Coole","orcid":"0000-0002-8821-4139","position":2,"is_corresponding":false},{"id":294095,"name":"Melody T. Tan","orcid":"0000-0001-9918-4062","position":3,"is_corresponding":false},{"id":294096,"name":"Xuan Zhao","orcid":"0000-0003-1660-5605","position":4,"is_corresponding":false},{"id":296469,"name":"Hawraa Badaoui","orcid":null,"position":5,"is_corresponding":false},{"id":34016,"name":"Jacob T. Robinson","orcid":"0000-0002-3509-3054","position":6,"is_corresponding":false},{"id":294097,"name":"Michelle D. Williams","orcid":"0000-0002-9133-7332","position":7,"is_corresponding":false},{"id":369392,"name":"Nadarajah Vigneswaran","orcid":"0000-0002-6995-1918","position":8,"is_corresponding":false},{"id":294098,"name":"Ann M. Gillenwater","orcid":"0000-0002-0935-0037","position":9,"is_corresponding":false},{"id":294099,"name":"Rebecca Richards‐Kortum","orcid":"0000-0003-2347-9467","position":10,"is_corresponding":false},{"id":254314,"name":"Ashok Veeraraghavan","orcid":"0000-0001-5043-7460","position":11,"is_corresponding":false},{"id":296468,"name":"Lingbo Jin","orcid":null,"position":0,"is_corresponding":true}],"reference_count":55,"raw_metadata":null,"created_at":"2026-07-19T01:58:01.889748Z","pmid":"38580633","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":[]}