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 …
Vision Transformers in medical computer vision—A contemplative retrospection
Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …
contained within images, have evolved as one of the most contemporary and dominant …
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 …
A topological loss function for deep-learning based image segmentation using persistent homology
We introduce a method for training neural networks to perform image or volume
segmentation in which prior knowledge about the topology of the segmented object can be …
segmentation in which prior knowledge about the topology of the segmented object can be …
Applications of artificial intelligence in cardiovascular imaging
M Sermesant, H Delingette, H Cochet, P Jaïs… - Nature Reviews …, 2021 - nature.com
Research into artificial intelligence (AI) has made tremendous progress over the past
decade. In particular, the AI-powered analysis of images and signals has reached human …
decade. In particular, the AI-powered analysis of images and signals has reached human …
Triplet attention and dual-pool contrastive learning for clinic-driven multi-label medical image classification
Multi-label classification (MLC) can attach multiple labels on single image, and has
achieved promising results on medical images. But existing MLC methods still face …
achieved promising results on medical images. But existing MLC methods still face …
Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the
general population. Low dose computed tomography (LDCT) for lung cancer screening …
general population. Low dose computed tomography (LDCT) for lung cancer screening …
Medical image segmentation with limited supervision: a review of deep network models
J Peng, Y Wang - IEEE Access, 2021 - ieeexplore.ieee.org
Despite the remarkable performance of deep learning methods on various tasks, most
cutting-edge models rely heavily on large-scale annotated training examples, which are …
cutting-edge models rely heavily on large-scale annotated training examples, which are …
A novel multi-attention, multi-scale 3D deep network for coronary artery segmentation
Automatic segmentation of coronary arteries provides vital assistance to enable accurate
and efficient diagnosis and evaluation of coronary artery disease (CAD). However, the task …
and efficient diagnosis and evaluation of coronary artery disease (CAD). However, the task …
Graph convolutional networks for coronary artery segmentation in cardiac CT angiography
Detection of coronary artery stenosis in coronary CT angiography (CCTA) requires highly
personalized surface meshes enclosing the coronary lumen. In this work, we propose to use …
personalized surface meshes enclosing the coronary lumen. In this work, we propose to use …