Explainable artificial intelligence: a comprehensive review
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
A review of medical image data augmentation techniques for deep learning applications
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …
prevalence in natural language processing or computer vision. Since medical imaging bear …
Fast and low-GPU-memory abdomen CT organ segmentation: the flare challenge
Automatic segmentation of abdominal organs in CT scans plays an important role in clinical
practice. However, most existing benchmarks and datasets only focus on segmentation …
practice. However, most existing benchmarks and datasets only focus on segmentation …
Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks
Coronavirus is an epidemic that spreads very quickly. For this reason, it has very devastating
effects in many areas worldwide. It is vital to detect COVID-19 diseases as quickly as …
effects in many areas worldwide. It is vital to detect COVID-19 diseases as quickly as …
[HTML][HTML] Physical interpretation of machine learning-based recognition of defects for the risk management of existing bridge heritage
The challenge of the research work presented in the paper is to combine the growing
interest in monitoring the health condition of existing bridge heritage through systematic and …
interest in monitoring the health condition of existing bridge heritage through systematic and …
VerSe: a vertebrae labelling and segmentation benchmark for multi-detector CT images
Vertebral labelling and segmentation are two fundamental tasks in an automated spine
processing pipeline. Reliable and accurate processing of spine images is expected to …
processing pipeline. Reliable and accurate processing of spine images is expected to …
Deep learning-based regression and classification for automatic landmark localization in medical images
In this study, we propose a fast and accurate method to automatically localize anatomical
landmarks in medical images. We employ a global-to-local localization approach using fully …
landmarks in medical images. We employ a global-to-local localization approach using fully …
Web-based fully automated cephalometric analysis by deep learning
Abstract Background and Objective An accurate lateral cephalometric analysis is vital in
orthodontic diagnosis. Identification of anatomic landmarks on lateral cephalograms is …
orthodontic diagnosis. Identification of anatomic landmarks on lateral cephalograms is …
Structured landmark detection via topology-adapting deep graph learning
Image landmark detection aims to automatically identify the locations of predefined fiducial
points. Despite recent success in this field, higher-ordered structural modeling to capture …
points. Despite recent success in this field, higher-ordered structural modeling to capture …