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Prediction-based coding with rate control for lossless region of interest in pathology imaging
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Bartrina-Rapesta, Joan, Hernández-Cabronero, Miguel, Sanchez Silva, Victor, Serra-Sagristà, Joan, Jamshidi, Pouya and Castellani, J. (2024) Prediction-based coding with rate control for lossless region of interest in pathology imaging. Signal Processing: Image Communication, 123 . 117087. doi:10.1016/j.image.2023.117087 ISSN 0923-5965.
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Official URL: https://doi.org/10.1016/j.image.2023.117087
Abstract
Online collaborative tools for medical diagnosis produced from digital pathology images have experimented an increase in demand in recent years. Due to the large sizes of pathology images, rate control (RC) techniques that allow an accurate control of compressed file sizes are critical to meet existing bandwidth restrictions while maximizing retrieved image quality. Recently, some RC contributions to Region of Interest (RoI) coding for pathology imaging have been presented. These encode the RoI without loss and the background with some loss, and focus on providing high RC accuracy for the background area. However, none of these RC contributions deal efficiently with arbitrary RoI shapes, which hinders the accuracy of background definition and rate control. This manuscript presents a novel coding system based on prediction with a novel RC algorithm for RoI coding that allows arbitrary RoIs shapes. Compared to other methods of the state of the art, our proposed algorithm significantly improves upon their RC accuracy, while reducing the compressed data rate for the RoI by 30%. Furthermore, it offers higher quality in the reconstructed background areas, which has been linked to better clinical performance by expert pathologists. Finally, the proposed method also allows lossless compression of both the RoI and the background, producing data volumes 14% lower than coding techniques included in DICOM, such as HEVC and JPEG-LS.
Item Type: | Journal Article | |||||||||||||||||||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RB Pathology R Medicine > RC Internal medicine T Technology > TA Engineering (General). Civil engineering (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | |||||||||||||||||||||
SWORD Depositor: | Library Publications Router | |||||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Diagnostic imaging -- Digital techniques, Pathology -- Technological innovations, Image processing -- Digital techniques, Image compression , Coding theory | |||||||||||||||||||||
Journal or Publication Title: | Signal Processing: Image Communication | |||||||||||||||||||||
Publisher: | Elsevier | |||||||||||||||||||||
ISSN: | 0923-5965 | |||||||||||||||||||||
Official Date: | April 2024 | |||||||||||||||||||||
Dates: |
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Volume: | 123 | |||||||||||||||||||||
Article Number: | 117087 | |||||||||||||||||||||
DOI: | 10.1016/j.image.2023.117087 | |||||||||||||||||||||
Status: | Peer Reviewed | |||||||||||||||||||||
Publication Status: | Published | |||||||||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||||||||
Date of first compliant deposit: | 12 March 2024 | |||||||||||||||||||||
Date of first compliant Open Access: | 15 March 2024 | |||||||||||||||||||||
RIOXX Funder/Project Grant: |
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