Successfully conducted the 22nd International Conference on Intelligent Systems Design and Applications (ISDA’22); 22nd International Conference on Hybrid Intelligent Systems (HIS’22); 18th International Conference on Information Assurance and Security (IAS’22); 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR’22); 14th World Congress on Nature and Biologically Inspired Computing (NaBIC’22); 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA’22) and 12th World Congress on Information and Communication Technologies (WICT’22) during December 12-16, 2022. Received papers from nearly 65 countries and the summary of accepted papers is as follows:

• ISDA 2022: 224 Papers from 47 countries
• HIS 2022: 97 Papers from 28 Countries
• IAS 2022: 26 Papers from 14 Countries
• SoCPaR 2022: 69 Papers from 20 Countries
• NaBIC 2022: 19 Papers from 14 countries
• IBICA 2022: 52 Papers from 22 Countries
• WICT 2022: 32 papers from 15 Countries

Enhancing the quality of medical images

Abstract: One of the challenging and the primary stages of medical image examination is the identification of the source of any disease, which may be the aberrant damage or change in tissue or organ caused by infections, injury, and a variety of other factors. Any such condition related to skin or brain sometimes advances in cancer and becomes a life-threatening disease. So, an efficient automatic image segmentation approach is required at the initial stage of medical image analysis. We introduced a new minimum generalized cross entropy as an objective function, with the inclusion of the degree of divergence. Another key contribution is the development of a new optimizer for improving the performance. The suggested multilevel thresholding approach is carried out on two different types of medical images – Brain MRI and dermoscopic images and found superior to other entropy-based thresholding methods.

Journal: Computers in Biology and Medicine
Authors: Bibekananda Jena et al.
DOI: 10.1016/j.compbiomed.2022.106214

Project title: Hybrid Blind Deconvolution and DeepOrganNet Techniques for Reconstructing 3D Molecular Structure of Genuine and Falsified Medicine Microscopic Images

Funded by: Govt of Malaysia
Funding period: 2021 - 2023