The aim of digital image processing is to improve the quality of image and subsequently to
perform features extraction and classification. It is effectively used in computer vision …

The improvement of Artificial Intelligence (AI) and Machine Learning (ML) can help
radiologists in tumor diagnostics without invasive measures. Magnetic resonance imaging …

In the event of damage to a structural system, ensuring the redistribution of loads becomes
crucial to mitigate the risk of progressive collapse. By providing alternative load paths …

Image Segmentation is the key process in medical imaging which produces different ROI
(Region of Interests) as per needed by the medical practitioner, who uses it for further …

This paper presents the sequential and parallel data decomposition strategies implemented
on a Particle Swarm Optimization (PSO) algorithm based Artificial Neural Network (PSO …

Multithreading has been shown to be a powerful approach for boosting a system
performance. One of the good examples of applications that benefits from multithreading is …

Brain tumours present a significant health challenge worldwide, necessitating accurate and
timely prediction for improved patient outcomes. ML techniques have emerged as promising …

Medical images are corrupted by different types of noises caused by the equipment itself. It
is very important to obtain precise images to facilitate accurate observations for the given …

Image segmentation is an image processing technique that divides an image into
contiguous regions or segments and typically used to locate objects and boundaries such as …

Medical data keeps growing with the growing number of scans every year. Patient
experience plays a vital role in development of healthcare technologies. The speed with …