ArticleFrontiers in molecular biosciences2020
Mass Detection and Segmentation in Digital Breast Tomosynthesis Using 3D-Mask Region-Based Convolutional Neural Network: A Comparative Analysis.
Article in Frontiers in molecular biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Deep learning, radiomics and radiogenomics applications in the digital breast tomosynthesis: a systematic review.BMC bioinformatics · 2023Pooled it
- Synthetic-to-Clinical Ensemble Learning for Volumetric Breast Tumor Segmentation in Digital Breast Tomosynthesis Under Limited Annotated Data.Diagnostics (Basel, Switzerland) · 2026Article
- Direct Segmentation of Mammography and Tomosynthesis Sinograms for Lesion Localization.Tomography (Ann Arbor, Mich.) · 2026Article
- Enhanced temporal encoding-decoding for survival analysis of multimodal clinical data in smart healthcare.Visual computing for industry, biomedicine, and art · 2025Article
- Deep Learning in Digital Breast Tomosynthesis: Current Status, Challenges, and Future Trends.MedComm · 2025Review
- Cross-Attention Adaptive Feature Pyramid Network with Uncertainty Boundary Modeling for Mass Detection in Digital Breast Tomosynthesis.Bioengineering (Basel, Switzerland) · 2025Article
- Review
- Breast Tumor Detection and Diagnosis Using an Improved Faster R-CNN in DCE-MRI.Bioengineering (Basel, Switzerland) · 2024Article
- A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis.JAMA network open · 2023Article
- Overlapped tobacco shred image segmentation and area computation using an improved Mask RCNN network and COT algorithm.Frontiers in plant science · 2023Article
- Artificial intelligence in clinical research of cancers.Briefings in bioinformatics · 2022Article
- SlypNet: Spikelet-based yield prediction of wheat using advanced plant phenotyping and computer vision techniques.Frontiers in plant science · 2022Article
- Analysis of the Diagnosis Model of Peripheral Non-Small-Cell Lung Cancer under Computed Tomography Images.Journal of healthcare engineering · 2022Article
- A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images.JAMA network open · 2021Article
- Computed Tomography Image under Convolutional Neural Network Deep Learning Algorithm in Pulmonary Nodule Detection and Lung Function Examination.Journal of healthcare engineering · 2021Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital breast tomosynthesis (DBT) is an emerging breast cancer screening and diagnostic modality that uses quasi-three-dimensional breast images to provide detailed assessments of the dense tissue within the breast. In this study, a framework of a 3D-Mask region-based convolutional neural network (3D-Mask RCNN) computer-aided diagnosis (CAD) system was developed for mass detection and segmentation with a comparative analysis of performance on patient subgroups with different clinicopathological characteristics. To this end, 364 samples of DBT data were used and separated into a training dataset (
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Registered trials
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