Neuro App: AI-driven 4D brain image processing on standalone platforms

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Jayasree Varadarajan and Md Abu Sufian

Manchester Metropolitan University, UK

: J Comput Eng Inf Technol

Abstract

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In the continuously evolving landscape of neuroimaging, the ability to process and analyze intricate 4D brain images is crucial. Our research project group developed "NeuroApp", which emerges as a cutting-edge solution, leveraging AI to process 4D brain images on standalone platforms, thus eliminating the constraints and dependencies of web-based systems. As we embarked on this journey, our goal was to bridge the gap between complex AI processing and the practical needs of researchers and clinicians. During the course of our research, we meticulously integrated advanced machine learning algorithms into NeuroApp. Through rigorous testing and iterations, we achieved a balance between efficient data preprocessing and enhanced image clarity. Our efforts culminated in a user-friendly application, replete with interactive visualization tools. Throughout the development process, we prioritized real-time computational capabilities. By leveraging GPU acceleration, we were able to significantly expedite AI computations, leading to real-time analysis. Furthermore, as we navigated the challenges of data security, we fortified NeuroApp with robust protocols to safeguard sensitive medical data. The feedback loop we established allowed for continuous improvement, ensuring our tool met the evolving needs of the neuroimaging community. One of the crowning achievements of our research was the modular architecture of NeuroApp. This design decision not only facilitates current functionalities but also paves the way for future integrations and advancements. Our research and the subsequent development of NeuroApp represent a significant stride in 4D neuroimaging. The results, both in terms of the model's performance and its real-world applicability, attest to the transformative potential of integrating AI with standalone applications in the realm of brain imaging. Keywords: Neuroimaging, NeuroApp, 4D brain images, Machine learning algorithms, GPU acceleration, AI, Modular architecture, Standalone applications. Recent Publications: 1. Design of Ultrasound Biomicroscopy in Open Platform Using FPGA Conference Name: Second International Conference On Science, Engineering and Management, 2014 Part of ISBN: 9789380530-70-3 2. Sufian, M. A. (2022)."The Impact of Consumer Decision Making Process towards Apparel Buying in the U.K". International Journal of Scientific Research and Engineering Development, ijsred, Volume 5 Issue 3, Page(s): 1241-1269 3. Sufian, M. A. (2016)."Comparative Study Of Fastness Properties And Color Absorbance Criteria Of Conventional And Avitera Reactive Dyeing On Cotton Knit Fabric". European Scientific Journal, ESJ, 12(15), 352. 4. Sufian, M. A. (2016). "Mercerization Techniques and Their Impact on Textile Properties: A Comprehensive Comparison of Different Parameters Based on the Insights from Textile Learner", Textile Learner, tl, Available at: https://textilelearner. net/development-of-mercerization-with-different-parameter/ December 1, one-stop solutions for textiles. 5. Enhancing Prediction and Analysis of UK Road Traffic Accident Severity Using AI: Integration of Machine Learning, Econometric Techniques, and Time Series Forecasting in Public Health Research Elsevier - Analytical Methods in Accident Research Journal 2023-11-10 | Working paper Authors: Jayasree Varadarajan, Md Abu Sufian.

Biography

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Jayasree Varadarajan, based in Leeds, UK, is an AI Technical solution developer with a passion for supporting SMEs/MSEs. With a strong background in understanding business needs and managing expectations, I excel in delivering customized AI tools to drive business development. Having gained extensive experience in supporting AI technologies for businesses, I possess the expertise to provide solution design and implementation using various coding tools, including data engineering and proof of concept applications. I work closely with other technical members to automate innovation processes, constantly seeking new tools and leveraging data to drive efficiency and effectiveness. I helped to empower businesses with AI tools, helping them unlock their full potential, and achieve sustainable growth.