Large-scale Medical Image Analysis
The main objective of this project is to develop a large–scale analysis framework enabling transferring 2D visual data analysis techniques to very large scales but also to 3D, 4D and multimodal imaging with high efficiency, and by increasing the scalability of existing tools and algorithms to large amounts of data.
The goal is to reduce the execution time of image analysis tasks and enhance interactions with end–users by selecting the right underlying infrastructures such as centralized servers, distributed clusters or even cloud computing. Bandwidth, storage capacity, processor power and main memory may all have their limiting effects and choosing an infrastructure should be facilitated with the results of LaMIA.
Although the developed techniques have an application focus on medical image analysis and retrieval, they are expected to provide tools for managing visual information in a large variety of domains from fundamental research to industrial applications.