ArticleJournal of biophotonics2024
Real-time breast lesion classification combining diffuse optical tomography frequency domain data and BI-RADS assessment.
Article in Journal of biophotonics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- AI-assisted diffuse correlation tomography for identifying breast cancer.Journal of biomedical optics · 2025Article
- In vivo optimization of the experimental conditions for the non-invasive optical assessment of breast density.Scientific reports · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated potential for breast cancer diagnosis, in which real-time or near real-time diagnosis with high accuracy is desired. However, DOT's relatively slow data processing and image reconstruction speeds have hindered real-time diagnosis. Here, we propose a real-time classification scheme that combines US breast imaging reporting and data system (BI-RADS) readings and DOT frequency domain measurements. A convolutional neural network is trained to generate malignancy probability scores from DOT measurements. Subsequently, these scores are integrated with BI-RADS assessments using a support vector machine classifier, which then provides the final diagnostic output. An area under the receiver operating characteristic curve of 0.978 is achieved in distinguishing between benign and malignant breast lesions in patient data without image reconstruction.
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