Medical Image Analysis Research (MIAR) Lab

The Medical Image Analysis Lab focuses on three key areas: breast cancer detection, ultrasound-guided needle tracking for medical interventions, and the development of assistive technology devices for patients with cerebral palsy (CP). The breast cancer detection research direction is focused on utilizing advanced image processing and machine learning techniques to analyze ultrasound breast images with the goal of enhancing the accuracy of breast cancer diagnostics, allowing for earlier and precise identification and outlining of cancerous tumors. The ultrasound-guided needle tracking research direction aims to develop advanced machine learning tools to enable the medical doctors and surgent to perform needle insertion interventions with greater targeting precision and high patient comfort and safety. Additionally, the CP assistive technology research direction is focused on developing innovative assistive devices tailored to the needs of CP patients to improve their mobility and independence as well as perform physical therapy exercises in a game-based interactive environment. The lab aims to integrate cutting-edge computing and machine learning technologies with clinical applications to improve the medical procedure, enhance patient comfort and safety, and advance the fields of computer-based medical diagnosis and therapy.