[HTML][HTML] A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities
Administrative and medical processes of the healthcare organizations are rapidly changing
because of the use of artificial intelligence (AI) systems. This change demonstrates the …
because of the use of artificial intelligence (AI) systems. This change demonstrates the …
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 …
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …
death cases and affected all sectors of human life. With gradual progression of time, COVID …
Medical image segmentation using deep learning: A survey
Deep learning has been widely used for medical image segmentation and a large number of
papers has been presented recording the success of deep learning in the field. A …
papers has been presented recording the success of deep learning in the field. A …
[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 …
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation
The medical imaging literature has witnessed remarkable progress in high-performing
segmentation models based on convolutional neural networks. Despite the new …
segmentation models based on convolutional neural networks. Despite the new …
A machine learning-based framework for diagnosis of COVID-19 from chest X-ray images
Abstract Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and
mankind all over the world is vulnerable to this virus. Alternative tools are needed that can …
mankind all over the world is vulnerable to this virus. Alternative tools are needed that can …
Deep learning for segmentation using an open large-scale dataset in 2D echocardiography
Delineation of the cardiac structures from 2D echocardiographic images is a common
clinical task to establish a diagnosis. Over the past decades, the automation of this task has …
clinical task to establish a diagnosis. Over the past decades, the automation of this task has …
A survey on incorporating domain knowledge into deep learning for medical image analysis
Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
Automatic multi-organ segmentation on abdominal CT with dense V-networks
Automatic segmentation of abdominal anatomy on computed tomography (CT) images can
support diagnosis, treatment planning, and treatment delivery workflows. Segmentation …
support diagnosis, treatment planning, and treatment delivery workflows. Segmentation …