RATIONALE AND OBJECTIVES: Artificial intelligence (AI) has the potential to transform the clinical practice of radiology. This study investigated Canadian medical students' perceptions of the impact of AI on radiology, and their influence on the stud...
RATIONALE AND OBJECTIVES: We propose an automated segmentation pipeline based on deep learning for proton lung MRI segmentation and ventilation-based quantification which improves on our previously reported methodologies in terms of computational eff...
RATIONALE AND OBJECTIVES: With the growing adoption of digital breast tomosynthesis (DBT) in breast cancer screening, we compare the performance of deep learning computer-aided diagnosis on DBT images to that of conventional full-field digital mammog...
As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, ...
RATIONALE AND OBJECTIVES: To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four hea...
Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools...
RATIONALE AND OBJECTIVES: Long-term survival after lung transplantation (LTx) is limited by bronchiolitis obliterans syndrome (BOS), defined as a sustained decline in forced expiratory volume in the first second (FEV) not explained by other causes. W...
RATIONALE AND OBJECTIVES: We evaluate utilizing convolutional neural networks (CNNs) to optimally fuse parenchymal complexity measurements generated by texture analysis into discriminative meta-features relevant for breast cancer risk prediction.
RATIONALE AND OBJECTIVES: Because it is imperative for understanding the performance of dual-energy computed tomography scanner to determine clinical diagnosis, we aimed to assess the accuracy of quantitative measurements using dual-energy computed t...
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