The Potential of Deep Learning to Revolutionize Current Breast MRI Practice

Article Radiology, Nuclear Medicine & Medical Imaging

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial

Erik Verburg et al.

Summary: This study developed an automated triaging method using deep learning to dismiss nearly 40% of MRI examinations without lesions in women with dense breasts, while still identifying malignant disease without missing any cancers.

RADIOLOGY (2022)

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Review Radiology, Nuclear Medicine & Medical Imaging

Application of Deep Learning in Breast Cancer Imaging

Luuk Balkenende et al.

Summary: This review provides an overview of the current state of deep learning research in breast cancer imaging. Breast imaging is crucial for early detection, monitoring, and evaluating breast cancer. Digital mammography, digital breast tomosynthesis, ultrasound, and magnetic resonance imaging are commonly used modalities for breast imaging, which can be digitized and applied with deep learning. Studies have shown that deep learning algorithms perform similarly or even better than radiologists in breast cancer imaging.

SEMINARS IN NUCLEAR MEDICINE (2022)

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Article Computer Science, Artificial Intelligence

Feasibility of Simulated Postcontrast MRI of Glioblastomas and Lower-Grade Gliomas by Using Three-dimensional Fully Convolutional Neural Networks

Evan Calabrese et al.

Summary: Simulated postcontrast T1-weighted brain MR images generated by a three-dimensional deep convolutional neural network were found to be similar to real acquired images in both quantitative and qualitative analysis, demonstrating high diagnostic accuracy.

RADIOLOGY-ARTIFICIAL INTELLIGENCE (2021)

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Review Radiology, Nuclear Medicine & Medical Imaging