Generative AI-Enhanced Microcalcification Detection in Full-Field Digital Mammography: Reducing False Positives with High Sensitivity

Abstract excerpt

<title>Abstract</title> <p>While generative AI shows promise across industries, its advantages over state-of-the-art segmentation AI in radiology remain unclear. This study addresses this gap by developing a generative AI model to refine calcification detection in full-field digital mammograms (FFDM), improving specificity while maintaining high sensitivity. A segmentation AI initially extracted calcification pix...

Topics

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• Artificial Intelligence
• Databases, Factual
• Deep Learning
• False Positive Reactions
• Forecasting
• Image Processing, Computer-Assisted
• Mutation
• Neoplasms

Identifiers and source

Literature Corpus work

44599f41-8f91-5e42-82b1-2325cc79a375

DOI

10.21203/rs.3.rs-7839897/v1