ArticleFrontiers in oncology2022
BUSnet: A Deep Learning Model of Breast Tumor Lesion Detection for Ultrasound Images.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The translational chasm in machine learning for triple-negative breast cancer: a quantitative landscape assessment.Frontiers in oncology · 2026Pooled it
- Ultrasound-Based AI in Predicting Hormone Receptor Status in Breast Cancer: Is "Digital Biopsy" Possible.Journal of imaging informatics in medicine · 2026Article
- Explainable AI based hybrid DRM-Net transfer learning model for breast cancer detection and classification using ultrasound images.Scientific reports · 2025Article
- YOLO AI model based on an automated breast volume scanner for the detection of benign and malignant breast lesions.Quantitative imaging in medicine and surgery · 2025Article
- Breast Cancer Classification with Various Optimized Deep Learning Methods.Diagnostics (Basel, Switzerland) · 2025Article
- Innovative breast cancer detection using a segmentation-guided ensemble classification framework.Biomedical engineering letters · 2025Article
- A Review of Artificial Intelligence in Breast Imaging.Tomography (Ann Arbor, Mich.) · 2024Review
- 3-D breast nodule detection on automated breast ultrasound using faster region-based convolutional neural networks and U-Net.Scientific reports · 2023Article
- An Automatic Breast Tumor Detection and Classification including Automatic Tumor Volume Estimation Using Deep Learning Technique.Asian Pacific journal of cancer prevention : APJCP · 2023Article
- Artificial Intelligence in Breast Ultrasound: From Diagnosis to Prognosis-A Rapid Review.Diagnostics (Basel, Switzerland) · 2022Review
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Authors and funding
5 authors.
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Abstract
Ultrasound (US) imaging is a main modality for breast disease screening. Automatically detecting the lesions in US images is essential for developing the artificial-intelligence-based diagnostic support technologies. However, the intrinsic characteristics of ultrasound imaging, like speckle noise and acoustic shadow, always degenerate the detection accuracy. In this study, we developed a deep learning model called BUSnet to detect the breast tumor lesions in US images with high accuracy. We first developed a two-stage method including the unsupervised region proposal and bounding-box regression algorithms. Then, we proposed a post-processing method to enhance the detecting accuracy further. The proposed method was used to a benchmark dataset, which includes 487 benign samples and 210 malignant samples. The results proved the effectiveness and accuracy of the proposed method.
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