Survey of Medical Image Compression Techniques and Comparative Analysis

2014 ◽

pp. 327-356

Author(s):

P. Geetha

Keyword(s):

Medical Imaging ◽

Image Compression ◽

Digital Imaging ◽

Medical Image ◽

Satellite Communications ◽

Digital Data ◽

High Definition ◽

Medical Image Compression ◽

High Definition Television ◽

Digital Storage

Today digital imaging is widely used in every application around us like Internet, High Definition TeleVision (HDTV), satellite communications, fax transmission, and digital storage of movies and more, because it provide superior resolution and quality. Recently, medical imaging has begun to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. However, medical imaging requires storing, communicating and manipulating large amounts of digital data. Applying image compression reduces the storage requirements, network traffic, and therefore improves efficiency. This chapter provides the need for medical image compression; different approaches to image compression, emerging wavelet based lossy-lossless compression techniques, how the existing recent compression techniques work and also comparison of results. After completing this chapter, the reader should have an idea of how to increase the compression ratio and at the same time maintain the PSNR level compared to the existing techniques, desirable features of standard compression techniques such as embededness and progressive transmission, how these are very useful and much needed in the interactive teleradiology, telemedicine and telebrowsing applications.

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A TWO COMPONENT MEDICAL IMAGE COMPRESSION TECHNIQUES FOR DICOM IMAGES

International Journal of Image Processing and Vision Science ◽

10.47893/ijipvs.2013.1043 ◽

2013 ◽

pp. 226-229

Author(s):

K. S. SELVANAYAKI

Keyword(s):

Image Compression ◽

Digital Imaging ◽

Medical Image ◽

High Speed ◽

Medical Images ◽

Set Partitioning ◽

The Body ◽

Compression Technique ◽

Medical Image Compression ◽

Two Component

To meet the demand for high speed transmission of image, efficient image storage, remote treatment an efficient image compression technique is essential. Wavelet theory has great potential in medical image compression. Most of the commercial medical image viewers do not provide scalability in image compression. This paper discusses a medical application that contains a viewer for digital imaging and communications in medicine (DICOM) images as a core module. Progressive transmission of medical images through internet has emerged as a promising protocol for teleradiology applications. The major issue that arises in teleradiology is the difficulty of transmitting large volume of medical data with relatively low bandwidth. Recent image compression techniques have increased the viability by reducing the bandwidth requirement and cost-effective delivery of medical images for primary diagnosis. This paper presents an effective algorithm to compress and reconstruct Digital Imaging and Communications in Medicine (DICOM) images. DICOM is a standard for handling, storing, printing and transmitting information in medical imaging. These medical images are volumetric consisting of a series of sequences of slices through a given part of the body. DICOM image is first decomposed by Haar Wavelet Decomposition Method. The wavelet coefficients are encoded using Set Partitioning in Hierarchical Trees (SPIHT) algorithm. Discrete Cosine Transform (DCT) is performed on the images and the coefficients are JPEG coded. The quality of the compressed image by different method are compared and the method exhibiting highest Peak Signal to Noise Ratio (PSNR) is retained for the image. The performance of the compression of medical images using the above said technique is studied with the two component medical image compression techniques.

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3D Medical Images Compression

Research Anthology on Recent Trends, Tools, and Implications of Computer Programming ◽

10.4018/978-1-7998-3016-0.ch048 ◽

2021 ◽

pp. 1046-1067

Author(s):

Mohamed Fawzy Aly ◽

Mahmood A. Mahmood

Keyword(s):

Medical Imaging ◽

Image Compression ◽

Medical Image ◽

Medical Images ◽

Medical Data ◽

The Body ◽

Medical Image Compression ◽

Diagnostic Data ◽

Digital Representations ◽

And Storage

Medical images are digital representations of the body. Medical imaging technology has improved tremendously in the past few decades. The amount of diagnostic data produced in a medical image is vast and as a result could create problems when sending the medical data through a network. To overcome this, there is a great need for the compression of medical images for communication and storage purposes. This chapter contains an introduction to compression types, an overview of medical image modalities, and a survey on coding techniques that deal with 3D medical image compression.

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Algorithm development and hardware implementation for medical image compression system: a review

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v18.i3.pp1331-1341 ◽

2020 ◽

Vol 18 (3) ◽

pp. 1331

Author(s):

Noor Huda Ja’afar ◽

Afandi Ahmad

Keyword(s):

Performance Evaluation ◽

Medical Imaging ◽

Image Compression ◽

Medical Image ◽

Hardware Implementation ◽

Medical Image Compression ◽

Algorithm Development ◽

Compression System ◽

Hardware Implementations ◽

Software And Hardware

<span>In the high-tech world, medical imaging is very important to diagnose and analyze illness inside human body. The increasing number of patients annually has continuously growth the amount of medical imaging data generated and directly causes a demand for data storage. Generally, medical images are rich with data, where these data are important for diagnosing purpose. However, some of the data represents redundant information and sometimes can be discarded. Thus, the research area on medical image compression dealing with three-dimensional (3-D) modalities need to be given more attention and exploration. The algorithm development using wavelet transform with software implementation are the famous topics explored among researchers, whilst fewer works have been done in utilizing curvelet transform in medical image compression. Along with that, very limited hardware implementation of 3-D medical image compression is discovered. In term of performance evaluation, most of the previous works conducted objective test compared with subjective test. To fill in this gap, medical image compression system will be reviewed, with the aim to identify the recent method used in medical image compression system. This paper thoroughly scrutinizes the recent advances in medical image compression mainly in terms of compression method, algorithm development with software and hardware implementations and performance evaluation. In conclusion, the overall picture of the medical image compression landscape, where most of the researchers more focused on algorithm development or software implementations without having the combination of software and hardware implementations.</span>

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3D Medical image compression using the quincunx wavelet coupled with SPIHT

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v18.i2.pp821-828 ◽

2020 ◽

Vol 18 (2) ◽

pp. 821

Author(s):

Benlabbes Haouari

Keyword(s):

Wavelet Transform ◽

Medical Imaging ◽

Image Compression ◽

Medical Image ◽

Medical Images ◽

Digital Technologies ◽

Visual Quality ◽

Medical Image Compression ◽

Coding Scheme

<p>Medical imaging is a growing field due to the development of digital technologies that produce 3D and even 4D data. The counterpart to the resolution offered by these voluminal images resides in the amount of gigantic data, hence the need for compression. This article presents a new coding scheme dedicated to 3D medical images. The originality of our approach lies in the application of the Quinqunx wavelet transform coupled with the SPIHT encoder on a database of medical images. This approach achieves much higher compression rates, while maintaining a very acceptable visual quality.</p>

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Lossless Hybrid Coding technique based on Quasi Fractal & Oscillation Concept Method for Medical Image Compression

International Journal of Computer Communication and Informatics ◽

10.34256/ijcci2015 ◽

2020 ◽

Vol 2 (1) ◽

pp. 38-48

Author(s):

Satyawati Magar ◽

Bhavani Sridharan

Keyword(s):

Image Compression ◽

Medical Image ◽

Vital Role ◽

Band Pass Filter ◽

Hybrid Technique ◽

Compression Technique ◽

Medical Image Compression ◽

Pass Filter ◽

Digital Storage ◽

Fast Development

The Image compression is the most important entity in various fields. Image compression plays vital role in many applications. Out of which biomedical is one of the challenging applications. In medical research, everyday there is fast development and advancement. Medical researchers are thinking about digital storage of data hence medical image compression has a crucial role in hospitals. Here Morphological filter & adaptive threshold are used for refinement and used Quasi Fractal & Oscillation concept for developing new hybrid algorithm. Oscillation concept is lossy image compression technique hence applied on Non-ROI. Quasi fractal is lossless image compression technique applied on ROI. The experimental results shows that better CR with acceptable PSNR has been achieved using hybrid technique based on Morphological band pass filter and Adaptive thresholding for ROI. Here, innovative hybrid technique gives the CR 24.61 which improves a lot than hybrid method using BTC-SPIHT is 5.65. Especially PSNR is also retained and bit improved i.e. 33.51. This hybrid technique gives better quality of an image.

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3D Medical Images Compression

Advances in Multimedia and Interactive Technologies - Intelligent Multidimensional Data and Image Processing ◽

10.4018/978-1-5225-5246-8.ch010 ◽

2018 ◽

pp. 259-279

Author(s):

Mohamed Fawzy Aly ◽

Mahmood A. Mahmood

Keyword(s):

Medical Imaging ◽

Image Compression ◽

Medical Image ◽

Medical Images ◽

Medical Data ◽

The Body ◽

Medical Image Compression ◽

Diagnostic Data ◽

Digital Representations ◽

And Storage

Medical images are digital representations of the body. Medical imaging technology has improved tremendously in the past few decades. The amount of diagnostic data produced in a medical image is vast and as a result could create problems when sending the medical data through a network. To overcome this, there is a great need for the compression of medical images for communication and storage purposes. This chapter contains an introduction to compression types, an overview of medical image modalities, and a survey on coding techniques that deal with 3D medical image compression.

Download Full-text