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
I want to sincerely thank you for funding my research this summer and for recognizing the value of my work in medical image processing with deep learning. Your support has been a driving force, allowing me to dive deeper into this innovative field and work on solutions that could make a real difference in healthcare. This experience has not only expanded my knowledge but also reinforced my belief that what I’m doing matters. Your generosity has given me the confidence to push forward, and I’m truly grateful for the opportunity you’ve provided.![Profile image of Dana Kim](https://research.berkeley.edu/wp-content/uploads/2024/05/Kim_Dana-400x400.jpg)