Context-Based Coding of Ultrasound Medical Images using Shape-Adaptive Transform Representation

Shira Nemirovsky-Rotman; Zvi Friedman; Moshe Porat

doi:10.1109/IUS52206.2021.9593468

Context-Based Coding of Ultrasound Medical Images using Shape-Adaptive Transform Representation

Shira Nemirovsky-Rotman, Zvi Friedman, Moshe Porat

Research output: Contribution to journal › Conference article › peer-review

Abstract

Image compression is essential in order to meet storage and transmission requirements for the vastly produced medical image data. While it is desirable to achieve high compression rates, it is crucial that important medical diagnostic details will be preserved. We introduce a new approach to processing medical images, in which Regions-Of-Interest (ROIs) are automatically detected and coded with relatively high bit rates, while the background is coded with low bit rates. Our coding algorithm is based on identifying the ROI pixels and division of the image into blocks, which are classified based on their ROI pixels contents. Each block is coded according to its classification, using Discrete Cosine Transform (DCT) or Shape Adaptive (SA)-DCT. In addition, we propose a tailored interpolation scheme, which significantly reduces artifacts created in ROI segments that are of irregular or noncontinuous shape. Results on echo-cardiac and fetal images demonstrate the performance of our method.

Original language	English
Journal	IEEE International Ultrasonics Symposium, IUS
DOIs	https://doi.org/10.1109/IUS52206.2021.9593468
State	Published - 2021
Externally published	Yes
Event	2021 IEEE International Ultrasonics Symposium, IUS 2021 - Virtual, Online, China Duration: 11 Sep 2011 → 16 Sep 2011

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the Israeli Ministry of Science and Technology and by the Ollendorff Minerva Centre of the Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering at the Technion - Israel Institute of Technology. Minerva is funded through the BMBF.

Publisher Copyright:
© 2021 IEEE.

Keywords

Image compression
Region-Of-Interest
Shape-Adaptive Discrete Cosine Transform
bit-rate
storage
transmission

ASJC Scopus subject areas

Acoustics and Ultrasonics

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10.1109/IUS52206.2021.9593468

Cite this

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title = "Context-Based Coding of Ultrasound Medical Images using Shape-Adaptive Transform Representation",

abstract = "Image compression is essential in order to meet storage and transmission requirements for the vastly produced medical image data. While it is desirable to achieve high compression rates, it is crucial that important medical diagnostic details will be preserved. We introduce a new approach to processing medical images, in which Regions-Of-Interest (ROIs) are automatically detected and coded with relatively high bit rates, while the background is coded with low bit rates. Our coding algorithm is based on identifying the ROI pixels and division of the image into blocks, which are classified based on their ROI pixels contents. Each block is coded according to its classification, using Discrete Cosine Transform (DCT) or Shape Adaptive (SA)-DCT. In addition, we propose a tailored interpolation scheme, which significantly reduces artifacts created in ROI segments that are of irregular or noncontinuous shape. Results on echo-cardiac and fetal images demonstrate the performance of our method.",

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AU - Porat, Moshe

N1 - Funding Information: ACKNOWLEDGMENT This work was supported by the Israeli Ministry of Science and Technology and by the Ollendorff Minerva Centre of the Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering at the Technion - Israel Institute of Technology. Minerva is funded through the BMBF. Publisher Copyright: © 2021 IEEE.

PY - 2021

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N2 - Image compression is essential in order to meet storage and transmission requirements for the vastly produced medical image data. While it is desirable to achieve high compression rates, it is crucial that important medical diagnostic details will be preserved. We introduce a new approach to processing medical images, in which Regions-Of-Interest (ROIs) are automatically detected and coded with relatively high bit rates, while the background is coded with low bit rates. Our coding algorithm is based on identifying the ROI pixels and division of the image into blocks, which are classified based on their ROI pixels contents. Each block is coded according to its classification, using Discrete Cosine Transform (DCT) or Shape Adaptive (SA)-DCT. In addition, we propose a tailored interpolation scheme, which significantly reduces artifacts created in ROI segments that are of irregular or noncontinuous shape. Results on echo-cardiac and fetal images demonstrate the performance of our method.

AB - Image compression is essential in order to meet storage and transmission requirements for the vastly produced medical image data. While it is desirable to achieve high compression rates, it is crucial that important medical diagnostic details will be preserved. We introduce a new approach to processing medical images, in which Regions-Of-Interest (ROIs) are automatically detected and coded with relatively high bit rates, while the background is coded with low bit rates. Our coding algorithm is based on identifying the ROI pixels and division of the image into blocks, which are classified based on their ROI pixels contents. Each block is coded according to its classification, using Discrete Cosine Transform (DCT) or Shape Adaptive (SA)-DCT. In addition, we propose a tailored interpolation scheme, which significantly reduces artifacts created in ROI segments that are of irregular or noncontinuous shape. Results on echo-cardiac and fetal images demonstrate the performance of our method.

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Context-Based Coding of Ultrasound Medical Images using Shape-Adaptive Transform Representation

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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