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 …
Generative adversarial network in medical imaging: A review
Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …
community due to their capability of data generation without explicitly modelling the …
Multi-scale self-guided attention for medical image segmentation
Even though convolutional neural networks (CNNs) are driving progress in medical image
segmentation, standard models still have some drawbacks. First, the use of multi-scale …
segmentation, standard models still have some drawbacks. First, the use of multi-scale …
Multi-label active learning-based machine learning model for heart disease prediction
The rapid growth and adaptation of medical information to identify significant health trends
and help with timely preventive care have been recent hallmarks of the modern healthcare …
and help with timely preventive care have been recent hallmarks of the modern healthcare …
3D deeply supervised network for automated segmentation of volumetric medical images
While deep convolutional neural networks (CNNs) have achieved remarkable success in 2D
medical image segmentation, it is still a difficult task for CNNs to segment important organs …
medical image segmentation, it is still a difficult task for CNNs to segment important organs …
Going deep in medical image analysis: concepts, methods, challenges, and future directions
Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …
technology has recently attracted so much interest of the Medical Imaging Community that it …
Introducing Biomedisa as an open-source online platform for biomedical image segmentation
We present Biomedisa, a free and easy-to-use open-source online platform developed for
semi-automatic segmentation of large volumetric images. The segmentation is based on a …
semi-automatic segmentation of large volumetric images. The segmentation is based on a …
A review on the use of deep learning for medical images segmentation
Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …
images. They have been used extensively for medical image segmentation as the first and …
[HTML][HTML] Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge
Abstract Knowledge of whole heart anatomy is a prerequisite for many clinical applications.
Whole heart segmentation (WHS), which delineates substructures of the heart, can be very …
Whole heart segmentation (WHS), which delineates substructures of the heart, can be very …
Applications of artificial intelligence in cardiovascular imaging
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 …