Compression of Images from Emergent Modalities
by IT on 07-07-2020
This is a IT internal project, developed in collaboration with BioImaging Austria and i3S – Instituto de Inovação e Investigção em Saúde, University of Porto. (see more)
The advances in the field of medical imaging have pushed the research institutes and medical facilities storage capabilities to the limit, with huge amounts of data being generated everyday. To cope with this issue, novel methods to compress the generated data must be developed. Such methods shall be among three categories: (i) lossless methods (whose output can be perfectly reversed in the original data); (ii) near-lossless methods (whose degradation in the resulting data cannot be perceived either by the human eye or does not impact the results of the automatic processing systems), (iii) lossy methods (in particular cases only a small segment of the data presents important data, so some distortion is acceptable in the remainder).
In line with these technological developments and requirements, the main goal of this project is the development of coding approaches specifically designed to alleviate data storage and transmission bottlenecks, which are emerging from the use of optical imaging modalities such as Light-Sheet Fluorescence Microscopy (LSFM), High-Resolution Episcopic Microscopy (HREM), and histological Whole-Slide Images (WSI), due to their data volumes, which individually may easily exceed few Terabytes of data.
Illustration: Data compression is the process of reducing overall size of the data so that it can be easily transmitted and stored