In Silico Digital Breast Tomosynthesis Dataset for the Comparative Analysis of Deep Learning Models in Tumor Segmentation.
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| Title: | In Silico Digital Breast Tomosynthesis Dataset for the Comparative Analysis of Deep Learning Models in Tumor Segmentation. |
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| Authors: | Alfaro Vergara C; Department of Medical Technology, Faculty of Health Sciences, Universidad de Tarapacá, Arica, Chile. calfarov@academicos.uta.cl.; Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile. calfarov@academicos.uta.cl., Araya Caro N; Department of Computer Sciences, Faculty of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile., Mery Quiroz D; Department of Computer Sciences, Faculty of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile.; Millennium Institute for Intelligent Healthcare Engineering i-Health, Santiago, Chile., Prieto Vasquez C; Millennium Institute for Intelligent Healthcare Engineering i-Health, Santiago, Chile.; School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile. |
| Source: | Journal of imaging informatics in medicine [J Imaging Inform Med] 2026 Apr; Vol. 39 (2), pp. 1519-1535. Date of Electronic Publication: 2025 Aug 04. |
| Publication Type: | Comparative Study; Journal Article |
| Journal Info: | Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2948-2933 |
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| DOI: | 10.1007/s10278-025-01626-z |
