{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T06:35:36Z","timestamp":1772692536267,"version":"3.50.1"},"reference-count":23,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T00:00:00Z","timestamp":1772496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003141","name":"Secretar\u00eda de Ciencia, Humanidades, Tecnolog\u00eda e Innovaci\u00f3n","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003141","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Tomography"],"abstract":"<jats:p>Background: The Detection and localization of breast lesions remain challenging in mammography and digital breast tomosynthesis (DBT) due to tissue overlap and information loss during volumetric reconstruction. Sinograms preserve the full angular projection data acquired during scanning, enabling analysis of tissue structure without reconstruction. Methods: This study proposes a direct segmentation approach for mammography and DBT sinograms using a U-Net architecture. Experiments were conducted on 1082 annotated mammography mass images from the CBIS-DDSM dataset (521 benign, 561 malignant) and 272 annotated DBT images from the Breast Cancer Screening DBT dataset (136 benign, 136 malignant). Dataset splitting was performed at the patient level to prevent data leakage, and all reported quantitative results correspond to the independent test set, with the validation set used solely for model selection and early stopping. Three input configurations were evaluated: mammography sinograms, DBT sinograms, and a combined model. Results: The mammography model achieved the highest performance (Dice: 0.94 training, 0.90 test), outperforming DBT alone (0.77 training, 0.70 test). Multimodal fusion improved DBT results (Dice: 0.84 test). Centroid analysis showed 99.11% correspondence with reference annotations (average distance: 2.83 pixels), and partial back-projection reconstructions confirmed anatomical consistency. Compared with YOLOv5x, the proposed approach provided superior lesion localization, particularly for small or multiple lesions. Conclusions: Direct sinogram segmentation is an efficient, clinically viable strategy for breast lesion detection and localization.<\/jats:p>","DOI":"10.3390\/tomography12030034","type":"journal-article","created":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T15:22:21Z","timestamp":1772551341000},"page":"34","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Direct Segmentation of Mammography and Tomosynthesis Sinograms for Lesion Localization"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8245-5898","authenticated-orcid":false,"given":"Estefan\u00eda Ru\u00edz","family":"Mu\u00f1oz","sequence":"first","affiliation":[{"name":"Instituto Nacional de Astrof\u00edsica, \u00d3ptica y Electr\u00f3nica, Sta. Mar\u00eda Tonantzintla, Puebla 72840, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0965-6420","authenticated-orcid":false,"given":"Leopoldo Altamirano","family":"Robles","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Astrof\u00edsica, \u00d3ptica y Electr\u00f3nica, Sta. Mar\u00eda Tonantzintla, Puebla 72840, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8487-0836","authenticated-orcid":false,"given":"Raquel D\u00edaz","family":"Hern\u00e1ndez","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Astrof\u00edsica, \u00d3ptica y Electr\u00f3nica, Sta. Mar\u00eda Tonantzintla, Puebla 72840, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8294-5926","authenticated-orcid":false,"given":"Kelsey Alejandra Ram\u00edrez","family":"Guti\u00e9rrez","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Astrof\u00edsica, \u00d3ptica y Electr\u00f3nica, Sta. Mar\u00eda Tonantzintla, Puebla 72840, Mexico"},{"name":"Secretaria de Ciencia, Humanidades, Tecnolog\u00eda e Innovaci\u00f3n (SECIHTI), Mexico City 03940, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1281-9040","authenticated-orcid":false,"given":"Sa\u00fal","family":"Zapotecas-Mart\u00ednez","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Astrof\u00edsica, \u00d3ptica y Electr\u00f3nica, Sta. Mar\u00eda Tonantzintla, Puebla 72840, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7070-5899","authenticated-orcid":false,"given":"Jos\u00e9 de Jes\u00fas","family":"Vel\u00e1zquez Arreola","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Astrof\u00edsica, \u00d3ptica y Electr\u00f3nica, Sta. Mar\u00eda Tonantzintla, Puebla 72840, Mexico"},{"name":"Secretaria de Ciencia, Humanidades, Tecnolog\u00eda e Innovaci\u00f3n (SECIHTI), Mexico City 03940, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,3]]},"reference":[{"key":"ref_1","unstructured":"(2022, April 09). Breast Cancer: Stages. 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Available online: https:\/\/inaoe.repositorioinstitucional.mx\/jspui\/handle\/1009\/2641."}],"container-title":["Tomography"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2379-139X\/12\/3\/34\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T05:15:30Z","timestamp":1772687730000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2379-139X\/12\/3\/34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,3]]},"references-count":23,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,3]]}},"alternative-id":["tomography12030034"],"URL":"https:\/\/doi.org\/10.3390\/tomography12030034","relation":{},"ISSN":["2379-139X"],"issn-type":[{"value":"2379-139X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,3]]}}}