The AI algorithm utilises deep learning techniques to evaluate multiple mammogram views simultaneously. Credit: University of Eastern Finland.

A research team from the University of Eastern Finland has developed MV-DEFEAT, an AI algorithm, to enhance breast cancer screening accuracy.

The AI algorithm holds the potential to transform radiological practices by improving mammogram density assessment.

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It utilises deep learning techniques to evaluate multiple mammogram views simultaneously, closely mirroring the decision-making process of radiologists.

Precise mammography interpretation is essential for breast cancer screening, but obstacles such as inconsistent radiological assessments and a global radiology deficit make this difficult.

The research team, including doctoral researcher Gudhe Raju and senior researcher Hamid Behravan, employed a multi-view deep evidential fusion approach, as part of a study.

This method combines elements of the Dempster-Shafer evidential theory and subjective logic to provide a comprehensive analysis of mammogram images from multiple views.

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MV-DEFEAT has demonstrated a 50.78% improvement in distinguishing between benign and malignant tumours over existing multi-view approaches, using the public VinDr-Mammo dataset, which contains more than 10,000 mammograms.

The algorithm’s effectiveness has been consistent across different datasets, indicating its robust performance and adaptability to diverse patient demographics.

Its gradient-based saliency maps highlight regions of interest within the mammograms, aiding radiologists in decision-making.

These results highlight the potential of AI to enhance diagnostic processes, potentially leading to earlier detection and improved patient outcomes in breast cancer care.

Raju said: “To fully integrate AI like MV-DEFEAT into clinical practice, it is crucial to build trust among healthcare professionals through rigorous testing and validation. Indeed, our next steps involve further validation studies to establish MV-DEFEAT as a reliable tool for breast cancer diagnostics in Finland.”