Dana Kim L&S Math & Physical Sciences
Development of a medical image processing model using deep learning
My research focuses on developing and implementing advanced deep-learning models to significantly enhance the interpretative accuracy and efficiency of medical imaging, thereby improving disease diagnosis processes. This initiative addresses the urgent need for sophisticated diagnostic tools capable of managing complex diseases effectively and seeks to overcome the limitations associated with human-dependent analysis. The research utilizes a diverse array of medical images such as MRIs, CT scans, and X-rays as primary data for the training and refinement of algorithms. The research methodology is organized into distinct phases: Data Collection and Labeling, Image Loading and Pre-processing, Classification and Regression, Segmentation and Detection, Instance Segmentation and Image Enhancement, Model Validation and Evaluation, Integration, and Feedback Incorporation and Iterative Improvement. By enhancing both the accuracy and speed of medical image analysis through deep learning, this project promises substantial benefits for patient outcomes and aims to significantly reduce the workload of medical professionals, facilitating more timely and accurate medical interventions.
Message To Sponsor
Thank you for your generous support of my research project. Your contribution plays a crucial role in advancing the development and implementation of innovative deep-learning models for medical imaging. This work promises to significantly enhance disease diagnosis and improve patient care. I am deeply grateful for your commitment to fostering groundbreaking research and technology.