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Graph-Based Rate Control in Pathology Imaging With Lossless Region of Interest Coding
IEEE Transactions on Medical Imaging
|July 12, 2018
Summary
A new graph-based rate control algorithm enables lossless region of interest coding for digital pathology images. This method efficiently manages file sizes, enhancing telepathology collaboration by meeting storage and bandwidth needs.
Area of Science:
- Digital pathology
- Medical imaging
- Computer science
Background:
- Digital pathology images are crucial for multidisciplinary collaboration.
- Telepathology facilitates image sharing but faces challenges due to large file sizes.
- Rate control (RC) is essential for managing storage and bandwidth in telepathology.
Purpose of the Study:
- To develop a novel graph-based rate control algorithm for pathology images.
- To enable lossless coding for regions of interest (RoIs) while lossy compressing other areas.
- To improve the efficiency and accuracy of rate control in telepathology systems.
Main Methods:
- A graph-based algorithm representing image blocks as nodes.
- Utilizing a graph kernel to distribute bit budget among non-RoI blocks.
- Employing a rate-lambda (R-λ) model for rate-distortion curve approximation.
- Implementing the algorithm within the High-Efficiency Video Coding (HEVC) standard.
Main Results:
- The proposed algorithm accurately attains the target bit rate for non-RoI regions.
- It outperforms existing state-of-the-art methods for single image compression.
- Demonstrated effectiveness on a diverse range of pathology images with multiple RoIs.
Conclusions:
- The novel graph-based RC algorithm effectively balances lossless RoI coding with efficient non-RoI compression.
- This approach significantly enhances the potential of collaborative telepathology systems.
- Accurate rate control is achieved, addressing key limitations in digital pathology image transmission.
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