Advancements of Medical Image Enhancement in Healthcare Applications
1Shandong University, Jinan, China
2Tufts University, Boston, USA
3Beijing Institute of Technology, Beijing, China
4Emory University, Atlanta, USA
Advancements of Medical Image Enhancement in Healthcare Applications
Description
As one of the world’s largest and fastest-growing industries, healthcare engineering refers to all aspects of the prevention, diagnosis, treatment, and management of illness, as well as the preservation and improvement of physical and mental health and wellbeing through medical services.
Medical imaging technologies play more and more important roles not only in the diagnosis and treatment of diseases, but also in disease prevention, health checkup, major disease screening, health management, early diagnosis, disease severity evaluation, choice of treatment methods, treatment effect evaluation, and rehabilitation. The status of medical imaging technologies has increased continuously in healthcare applications.
Due to its ability to make the diagnosis and treatment of diseases, image guided surgery, and other medical links more timely, accurate, and efficient, medical image enhancement has become a routine task. Through producing excellent tissue uniformity, optimized contrast, edge enhancement, artifact elimination, intelligent noise reduction, and so forth, cutting-edge image enhancement helps doctors to accurately interpret medical images, a crucial foundation for better diagnosis and treatment.
The purpose of this special issue is to publish high-quality research articles as well as
reviews that seek to address recent development on medical image enhancement, denoising, edge sharpening, artifact elimination, and resolution enhancement, as well as relevant prospects on opportunities and challenges.
Potential topics include but are not limited to the following:
- Algorithms for medical image denoising: ultrasound, MRI, X-ray imaging, fundus photography, OCT, mammography, and so forth
- New methods of image sharpening and contrast enhancement
- Algorithms for artifact elimination: MRI, X-ray, CT, and so forth
- 2D/3D/4D image filtering and visualization: ultrasound, MRI, X-ray, CT, and OCT
- Algorithms for medical image resolution enhancement: interpolation and superresolution
- Molecular imaging filtering and fusion: PET, fMRI, ultrasound, and SPECT
- Optical microscopy and fluorescent imaging and enhancement