Compression of 3D MRI images based on symmetry in prediction-error field

Amraee, Somaieh; Karimi, Nader; Samavi, Shadrokh; Shirani, Shahram

doi:10.1109/icme.2011.6011897

Cited by 5 publications

(6 citation statements)

References 12 publications

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“…The proposed hybrid approach is illustrated as a block diagram in Figure 3. A new compression scheme based on symmetry in the field of prediction-error was reported in [58]. In order to provide an efficient method, both the intra and inter-slice correlations have been considered.…”

Section: Figurementioning

confidence: 99%

“…Figure 4 Block diagram of proposed method of six stages of compression algorithm [58] An analysis of the discrete fractional Fourier transform (DFT) based medical image compression using a hybrid encoding technique was discussed in [59]. This system comprises of the following phases namely encryption; domain transformation; SPIHT algorithm with Huffman compression; decoding through SPIHT with Huffman encoder and inverse fast two-dimensional fractional Fourier transform; and finally, the quasi-group decryption with Hadamard and number theoretic transform.…”

Section: Figurementioning

confidence: 99%

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Implementation Method on Medical Image Compression System: A Review

Muharam

Ahmad

2017

Jurnal Teknologi

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The rapid development of medical imaging and the invention of various medicines have benefited mankind and the whole community. Medical image processing is a niche area concerned with the operations and processes of generating images of the human body for clinical purposes. Potential areas such as image acquisition, image enhancement, image compression and storage, and image based visualization also include in medical image processing analysis. Unfortunately, medical image compression dealing with three-dimensional (3-D) modalities still in the pre-matured stage. Along with that, very limited researchers take a challenge to apply hardware on their implementation. Referring to the previous work reviewed, most of the compression method used lossless rather than lossy. For implementation using software, MATLAB and Verilog are the famous candidates among researchers. In term of analysis, most of the previous works conducted objective test compared with subjective test. This paper thoroughly reviews the recent advances in medical image compression mainly in terms of types of compression, software and hardware implementations and performance evaluation. Furthermore, challenges and open research issues are discussed in order to provide perspectives for future potential research. In conclusion, the overall picture of the image processing landscape, where several researchers more focused on software implementations and various combinations of software and hardware implementation.

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Section: Figurementioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Implementation Method on Medical Image Compression System: A Review

Muharam

Ahmad

2017

Jurnal Teknologi

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“…Since human anatomy has structural symmetry this feature can also be considered to compress 2D or 3D medical images [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Symmetry based perceptually lossless compression of 3D medical images in spatial domain

Chandrika

Aparna

David

2014

2014 International Conference on Computer, Communications, and Control Technology (I4CT)

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A perceptual model developed in spatial domain based on background luminance is combined with lossless compression frame work to remove visually redundant information. Block matching is applied on anatomical symmetry present in medical images to remove intra slice and inter slice correlations. The obtained results show better compression gains against lossless compression techniques, without any degradation in visual quality.

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“…In lossless compression of volumetric medical images an important number of technical advances have been reported [1,2,7,8,13,18,19,21,23]. Some of the existing works have assumed that all slices are independent and can be compressed separately.…”

mentioning

confidence: 99%

“…With telemedicine becoming more popular, there is also a need for reduction in transmission time of MRI images. Hence, compression of MRI images plays an important role for efficient storage and transmission [1,2,7,8,13,15,18,19,21,23].…”

mentioning

confidence: 99%

Use of symmetry in prediction-error field for lossless compression of 3D MRI images

Karimi

Samavi

Amraee

et al. 2014

Multimed Tools Appl

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Three dimensional MRI images which are powerful tools for diagnosis of many diseases require large storage space. A number of lossless compression schemes exist for this purpose. In this paper we propose a new approach for lossless compression of these images which exploits the inherent symmetry that exists in 3D MRI images. First, an efficient pixel prediction scheme is used to remove correlation between pixel values in an MRI image. Then a block matching routine is employed to take advantage of the symmetry within the prediction error image. Inter-slice correlations are eliminated using another block matching. Results of the proposed approach are compared with the existing standard compression techniques.

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Compression of 3D MRI images based on symmetry in prediction-error field

Cited by 5 publications

References 12 publications

Implementation Method on Medical Image Compression System: A Review

Implementation Method on Medical Image Compression System: A Review

Symmetry based perceptually lossless compression of 3D medical images in spatial domain

Use of symmetry in prediction-error field for lossless compression of 3D MRI images

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