Traditionally, pathology slides are handled by cutting a tissue sample into paper-thin sections, and staining them, so to bring out regions of interest (RoIs). Pathologists then put these thin sections on a glass slide to be analyzed under a microscope. Recent advances on whole-slide digital scanners have made possible the digitization of pathology slides, thus allowing storing them as digital images. Consequently, traditional analysis techniques that rely on pathologists looking under a microscope are rapidly being complemented by techniques that rely on pathologists looking at digital images on a monitor.
The digitization of pathology slides not only allows storing the imaging data for future research and clinical purposes, but also sharing them electronically for collaborative work. However, due to the high resolution required to digitize whole pathology slides, the resulting imaging data are usually very large in file size, which poses heavy demands on storage and transmission resources. Therefore, designing coding algorithms for efficient storage, access and transmission of whole-slide pathology images remains a challenge.
The main objective of this proposal is to design a coding algorithm capable of reducing both storage and transmission bandwidth requirements needed for archival and communication of whole-slide pathology images of tissue biopsies. The proposed algorithm will reduce the amount of data needed to represent these images, with no loss of information, while providing scalability and RoI coding capabilities. The algorithm will be based on integer wavelet transformation for data decorrelation, automatic image segmentation for RoI coding and layered entropy coding for scalability.
The successful completion of the proposed algorithm will facilitate the storage, access and transmission of whole-slide pathology images, which will increase their utility as an essential tool in the diagnosis and treatment of deadly diseases such as cancer.
Fields of science
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