Literature DB >> 35342283

COMPUTATIONAL 2D and 3D MEDICAL IMAGE DATA COMPRESSION MODELS.

S Boopathiraja1, V Punitha1, P Kalavathi1, V B Surya Prasath2,3,4,5.   

Abstract

In this world of big data, the development and exploitation of medical technology is vastly increasing and especially in big biomedical imaging modalities available across medicine. At the same instant, acquisition, processing, storing and transmission of such huge medical data requires efficient and robust data compression models. Over the last two decades, numerous compression mechanisms, techniques and algorithms were proposed by many researchers. This work provides a detailed status of these existing computational compression methods for medical imaging data. Appropriate classification, performance metrics, practical issues and challenges in enhancing the two dimensional (2D) and three dimensional (3D) medical image compression arena are reviewed in detail.

Entities:  

Keywords:  Compression Metrics; Computational Imaging; Lossless Compression; Lossy Compression; Medical Image Compression; Near-lossless Compression; Object based Compression Methods; Tensor Based compression Methods; Wavelets Based Compression Methods

Year:  2021        PMID: 35342283      PMCID: PMC8942405          DOI: 10.1007/s11831-021-09602-w

Source DB:  PubMed          Journal:  Arch Comput Methods Eng        ISSN: 1134-3060            Impact factor:   7.302


  26 in total

1.  Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms.

Authors:  Zixiang Xiong; Xiaolin Wu; Samuel Cheng; Jianping Hua
Journal:  IEEE Trans Med Imaging       Date:  2003-03       Impact factor: 10.048

2.  A wavelet-based region of interest encoder for the compression of angiogram video sequences.

Authors:  David Gibson; Michael Spann; Sandra I Woolley
Journal:  IEEE Trans Inf Technol Biomed       Date:  2004-06

3.  3-D scalable medical image compression with optimized volume of interest coding.

Authors:  Victor Sanchez; Rafeef Abugharbieh; Panos Nasiopoulos
Journal:  IEEE Trans Med Imaging       Date:  2010-06-17       Impact factor: 10.048

4.  Image compression using the 2-D wavelet transform.

Authors:  A S Lewis; G Knowles
Journal:  IEEE Trans Image Process       Date:  1992       Impact factor: 10.856

5.  Medical image compression by using three-dimensional wavelet transformation.

Authors:  J Wang; K Huang
Journal:  IEEE Trans Med Imaging       Date:  1996       Impact factor: 10.048

6.  High performance scalable image compression with EBCOT.

Authors:  D Taubman
Journal:  IEEE Trans Image Process       Date:  2000       Impact factor: 10.856

7.  TTHRESH: Tensor Compression for Multidimensional Visual Data.

Authors:  Rafael Ballester-Ripoll; Peter Lindstrom; Renato Pajarola
Journal:  IEEE Trans Vis Comput Graph       Date:  2019-03-08       Impact factor: 4.579

8.  High Bit-Depth Medical Image Compression With HEVC.

Authors:  Saurin S Parikh; Damian Ruiz; Hari Kalva; Gerardo Fernandez-Escribano; Velibor Adzic
Journal:  IEEE J Biomed Health Inform       Date:  2017-01-27       Impact factor: 5.772

9.  Lossless Compression on MRI Images Using SWT.

Authors:  V Anusuya; V Srinivasa Raghavan; G Kavitha
Journal:  J Digit Imaging       Date:  2014-10       Impact factor: 4.056

Review 10.  Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis.

Authors:  Benjamin Shickel; Patrick James Tighe; Azra Bihorac; Parisa Rashidi
Journal:  IEEE J Biomed Health Inform       Date:  2017-10-27       Impact factor: 5.772

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  1 in total

1.  Near Lossless Compression for 3D Radiological Images Using Optimal Multilinear Singular Value Decomposition (3D-VOI-OMLSVD).

Authors:  S Boopathiraja; P Kalavathi; S Deoghare; V B Surya Prasath
Journal:  J Digit Imaging       Date:  2022-08-29       Impact factor: 4.903

  1 in total

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