AIMC Journal:
Academic radiology

Showing 291 to 300 of 317 articles

Influence of Artificial Intelligence on Canadian Medical Students' Preference for Radiology Specialty: ANational Survey Study.

Academic radiology
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...

Convolutional Neural Networks with Template-Based Data Augmentation for Functional Lung Image Quantification.

Academic radiology
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...

Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.

Academic radiology
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...

Convolutional Neural Network Based Breast Cancer Risk Stratification Using a Mammographic Dataset.

Academic radiology
RATIONALE AND OBJECTIVES: We propose a novel convolutional neural network derived pixel-wise breast cancer risk model using mammographic dataset.

Deep Learning in Radiology.

Academic radiology
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, ...

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

Academic radiology
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...

Toward Augmented Radiologists: Changes in Radiology Education in the Era of Machine Learning and Artificial Intelligence.

Academic radiology
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...

Machine Learning Algorithms Utilizing Quantitative CT Features May Predict Eventual Onset of Bronchiolitis Obliterans Syndrome After Lung Transplantation.

Academic radiology
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...

Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Academic radiology
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.

How Well Does Dual-energy CT with Fast Kilovoltage Switching Quantify CT Number and Iodine and Calcium Concentrations?

Academic radiology
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...