A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
[HTML][HTML] Deep learning for cardiac image segmentation: a review
Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
Calcium scoring at coronary CT angiography using deep learning
Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score
often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA …
often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA …
Learning tree-structured representation for 3D coronary artery segmentation
Extensive research has been devoted to the segmentation of the coronary artery. However,
owing to its complex anatomical structure, it is extremely challenging to automatically …
owing to its complex anatomical structure, it is extremely challenging to automatically …
Development and application of artificial intelligence in cardiac imaging
B Jiang, N Guo, Y Ge, L Zhang… - The British Journal of …, 2020 - academic.oup.com
In this review, we describe the technical aspects of artificial intelligence (AI) in cardiac
imaging, starting with radiomics, basic algorithms of deep learning and application tasks of …
imaging, starting with radiomics, basic algorithms of deep learning and application tasks of …
Artificial intelligence: improving the efficiency of cardiovascular imaging
Introduction Artificial intelligence (AI) describes the use of computational techniques to
mimic human intelligence. In healthcare, this typically involves large medical datasets being …
mimic human intelligence. In healthcare, this typically involves large medical datasets being …
[HTML][HTML] Deep reinforcement learning for cerebral anterior vessel tree extraction from 3D CTA images
Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel
occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to …
occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to …
Geometrical and deep learning approaches for instance segmentation of CFRP fiber bundles in textile composites
Abstract Segmenting micro-Computed Tomography (µCT) images of textile composites is a
necessary step before modeling the material at the mesoscale. However, the accurate …
necessary step before modeling the material at the mesoscale. However, the accurate …
An Anatomy-and Topology-Preserving Framework for Coronary Artery Segmentation
Coronary artery segmentation is critical for coronary artery disease diagnosis but
challenging due to its tortuous course with numerous small branches and inter-subject …
challenging due to its tortuous course with numerous small branches and inter-subject …