Guest Editors
Prof. Tao Zhou, North Minzu University, China
Prof. Huiyu Zhou, University of Leicester, UK
Prof. Chen Li, Northeastern University, China
Summary
Computer-aided diagnosis (CAD) has made considerable progress in the last decades, resulting in the development of several effective CAD systems. Recent advances in machine learning (ML) have opened up novel avenues for computer-assisted diagnosis of medical image. Additionally, improvements in ML techniques, the majority of which are based on Deep Learning (DL), have substantially impacted the performance of CAD systems.
Currently, the medical sector demands more creative technology to handle vast amounts of data and enhance the quality of service provided to patients. It also requires an intelligent system to identify early symptoms of multiple diseases and give suitable treatment. A significant recent breakthrough via DL techniques has garnered interest in academic research and business application groups. DL is the most rapidly expanding discipline of machine learning. Recent studies have shown that DL may dramatically improve the diagnosis prediction of contagious diseases. Hence, DL approaches can enhance the accuracy of CAD systems.
Both original research and reviews will be considered. The following subtopics are the particular interests of this special issue, including but not limited to:
Deep learning for Instance segmentation based on medical image (X ray, CT, MRI, Ultrasonic image, PET, SPCT)
Deep learning for Semantic segmentation based on medical image (X ray, CT, MRI, Ultrasonic image, PET, SPCT)
Deep learning for Object detection based on medical image (X ray, CT, MRI, Ultrasonic image, PET, SPCT)
Deep learning for Multimodal medical image fusion based on medical image (X ray, CT, MRI, Ultrasonic image, PET, SPCT)
Data security and user privacy solutions for medical image (X ray, CT, MRI, Ultrasonic image, PET, SPCT)
Deep learning for Computer Aided Diagnosis based on medical image (X ray, CT, MRI, Ultrasonic image, PET, SPCT)
Semi-Supervised deep learning for medical imaging
Transfer learning in medical imaging
Keywords
Computer-Aided Diagnosis, Deep Learning, Medical Image Segmentation, Medical Image Fusion, Medical Image Enhancement
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