ArticleScientific data2024
Curated benchmark dataset for ultrasound based breast lesion analysis.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- DynamicBUS: restoring temporal dynamics from static ultrasound for improved breast cancer diagnosis.NPJ breast cancer · 2026Article
- An explainable biomedical foundation model via large-scale concept-enhanced vision-language pretraining.Nature biomedical engineering · 2026Article
- An Explainable Multimodal Framework for Breast Ultrasound Report Generation Using Vision-Language Transformers.Journal of imaging · 2026Article
- A deep learning system for non-invasive breast cancer diagnosis with multimodal data.Nature biomedical engineering · 2026Article
- Breast Ultrasound AI Under Dataset Shift: A Patient-Leakage-Aware Benchmark.Diagnostics (Basel, Switzerland) · 2026Article
- Article
- DRSeg: a weakly supervised framework for breast ultrasound image segmentation.Scientific reports · 2026Article
- Article
- Segment anything small for ultrasound: Enhancing segmentation with non-generative augmentation.PLOS digital health · 2026Article
- A Data-Efficient Machine Learning Approach for Breast Ultrasound Lesion Classification Integrating Image-Derived Features and Sonographic Descriptors.Diagnostics (Basel, Switzerland) · 2026Article
- An Interpretable Ensemble Transformer Framework for Breast Cancer Detection in Ultrasound Images.Diagnostics (Basel, Switzerland) · 2026Article
- Automated Radiological Report Generation from Breast Ultrasound Images Using Vision and Language Transformers.Journal of imaging · 2026Article
- Cross-attention guided multi-modal network for breast ultrasound diagnosis incorporating objective clinical semantics.Frontiers in medicine · 2026Article
- Exploring free radiomics software tools: a multiparametric evaluation for cancer classification.BMC medical imaging · 2025Article
- The role of AI for improved management of breast cancer: Enhanced diagnosis and health disparity mitigation.Computer methods and programs in biomedicine · 2025Review
- A Dual-stage Deep Learning Framework for Breast Ultrasound Image Segmentation and Classification.Journal of medical systems · 2025Article
- XBusNet: Text-Guided Breast Ultrasound Segmentation via Multimodal Vision-Language Learning.Diagnostics (Basel, Switzerland) · 2025Article
- MIC: Breast Cancer Multi-label Diagnostic Framework Based on Multi-modal Fusion Interaction.Journal of imaging informatics in medicine · 2025Article
- A curated benchmark dataset for molecular identification based on genome skimming.Scientific data · 2025Article
- LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection.Bioengineering (Basel, Switzerland) · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A new detailed dataset of breast ultrasound scans (BrEaST) containing images of benign and malignant lesions as well as normal tissue examples, is presented. The dataset consists of 256 breast scans collected from 256 patients. Each scan was manually annotated and labeled by a radiologist experienced in breast ultrasound examination. In particular, each tumor was identified in the image using a freehand annotation and labeled according to BIRADS features and lexicon. The histopathological classification of the tumor was also provided for patients who underwent a biopsy. The BrEaST dataset is the first breast ultrasound dataset containing patient-level labels, image-level annotations, and tumor-level labels with all cases confirmed by follow-up care or core needle biopsy result. To enable research into breast disease detection, tumor segmentation and classification, the BrEaST dataset is made publicly available with the CC-BY 4.0 license.
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