Computer Vision in Healthcare Applications
1Jiangxi University of Finance and Economics, Nanchang, China
2Chonbuk National University, Jeonju, Republic of Korea
3Laureate Institute for Brain Research, Tulsa, USA
4South-Central University for Nationalities, Wuhan, China
Computer Vision in Healthcare Applications
Description
Medical imaging has attracted increasing attention in recent years due to its vital component in healthcare applications. The advancement in computer vision, such as multimodal image fusion, medical image segmentation, image registration, computer-aided diagnosis, image annotation, and image-guided therapy, has opened up many new possibilities for revolutionizing healthcare. Such areas include mobile healthcare, computer vision for predictive analytics and therapy, medical imaging, population health applications, and mobile devices as biometric sensors.
With this scope in mind, this special issue focuses on recent advances in the applications of computer vision techniques for healthcare. For this purpose, we solicit submission of original research contributions that advance computer vision methods for healthcare engineering, as well as review articles that will stimulate the continuing efforts to understand the problems usually encountered in this field.
Potential topics include but are not limited to the following:
- Medical image analysis for healthcare (such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning)
- Computer vision for predictive analytics and therapy
- Fundamental algorithms for medical images in healthcare applications, such as segmentation, registration, fusion, and classification
- Scalable, robust, data-driven, ensemble learning, deep learning algorithms for medical images
- Visualization, mining, and analysis of medical image collections
- Visualization for healthcare big data