Latest Approaches for Medical Image Analysis
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4398
Special Issue Editors
Interests: medical image analysis; computer vision
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Medical imaging is a broad field that involves image capture for diagnostic and therapeutic purposes. Processing and analyzing medical images are often used to visualize anatomy or assess the function of human organs, pinpoint areas of pathology, analyze biological and metabolic processes, develop treatment plans, and perform image-guided surgery. This powerful tool brings much-needed quantitative information, providing enhanced medical information to benefit patients without increasing the already high cost of healthcare. In addition, the large number of applications that rely on this technology has increased the need for efficient, accurate, and reliable algorithms for medical image processing and analysis, especially as imaging techniques become increasingly complex and the number of images that need to be processed increases. Deep learning, especially supervised learning using convolutional neural networks for classification or segmentation, has recently been fully embraced and established by most medical professionals as a necessary technique to aid clinical procedures. Recent advances in machine learning and computer vision, including new work on semi-supervised learning, weakly supervised learning, transfer learning, and unsupervised learning, may help address many problems, such as reducing the cost of collecting data annotations. New neural network structures such as Figure Neural Networks and improved CNN structures from Neural Architecture Search are also proposed to improve inference ability given the same data.
The main topic of this issue will be medical image analysis, with a focus on its recent applications and developments in the clinic. We also believe that there are many obstacles and problems for medical image analysis technology to revolutionize clinical practice.
Prof. Dr. Il Dong Yun
Dr. Walid Abdullah Al
Guest Editors
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