Submission Due Date
3/1/2022
Guest Editors
Manoj Diwakar, Graphic Era Deemed to be University, Dehradun, India
Prabhishek Singh, Amity University, India
Introduction
A new digital world brings about new technologies like machine learning and deep learning, and this further can provide intriguing and notable results with regards to circumstances that are yet unknown in the field of medical imaging. The machine learning and deep learning offers many answers to many problems found in medical imaging and health care applications. Medical imaging is a process in which various imaging procedures are used to collect visual information about the interior structures of the body to provide an assessment of the illness and to provide treatment to it. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. To quantify such large medical imaging data, machine learning and deep learning carried out different algorithms such as support vector machine, convolutional neural network etc to solve this problem. There are various applications of medical image analysis that include: medical image denoising, medical image super resolution, multi-modal image fusion, medical image registration, medical image segmentation, medical image super-resolution, diagnose abnormalities in medical images, medical image synthesis etc.
This special issue is meant to give an awareness of medical image analysis and many techniques and algorithms used to analyse medical data. It also focuses on current achievements and latest developments in medical imaging and health care applications and to identify latest cutting-edge techniques of machine learning and deep learning in this domain.
Objective
The major objectives of the special issue are to:
• Extract advance scientific research within the broad field of health care and medical image analysis problems; and
• Have experts, academicians, researchers, and scientists share their achievement stories and research issues for applying advanced machine learning and deep learning techniques to the real-world health care and medical image analysis problems. We invite submissions successfully applying unconventional machine learning and deep learning techniques to the real-time medical imaging and health care problems by addressing to life-saving issues.
Recommended Topics
• Medical (CT, MRI, Ultrasound..etc) Image reconstruction.
• Multi-modality Medical (CT, MRI, Ultrasound..etc) image fusion.
• Medical image retrieval.
• Machine learning and Deep learning based medical image analysis and enhancement.
• Development in healthcare application using machine learning and deep learning.
• Intelligent steganalysis for Medical image based on machine learning and deep learning.
• Medical Image forensics based on machine learning and deep learning.
• Robust, fragile, and semi-fragile watermarking for medical image processing
• Medical image denoising.
• Diseases Prediction and its classification.
• Diagnosis of fatal Disease.
• Abnormality Detection.
• 3D-medical imaging
• Brain, Chest, Breast, Cardiac, and Musculo-skeletal imaging using machine learning and deep learning.
• Machine Learning and Deep Learning techniques for medical image analysis.
• Population health and Patient progress management in Health Care Applications.
• Predicting and preventing risks in Health Care Applications
Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Recent Advances in Medical Image Analysis using Machine Learning and Deep Learning for Health Care Applications on or before March 1st, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.
All inquiries should be directed to the attention of:
Manoj Diwakar
Prabhishek Singh
Guest Editors
International Journal of Reliable and Quality E-Healthcare (IJRQEH)