3-D warped discrete cosine transform for MRI image compression

Prabhu, K.M.M.; Sridhar, K.; Mischi, Massimo; Bharath, H. N.

doi:10.1016/j.bspc.2012.04.004

Cited by 22 publications

(7 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The parameters PSNR and bpp are generally used for assessing the quality of the reconstructed image. Earlier studies [1][2][3][4][5][6][7][8]13,14] discussed the image compression and [4][5][6] addressed the compression of images. The results were obtained in the present study, using the preprocessing step followed by the bisection method including thresholding, the quantization, dequantization and the IDWT were compared with the 3-D transforms, such as discrete Hartley transform (DHT), discrete cosine transform (DCT) and discrete Fourier transform (DFT) [6].…”

Section: Discussionmentioning

confidence: 99%

“…The easy and reliable digital transmission and storage of biomedical images would be a tremendous boon to the medical practices. This can help in instant availability of earlier imaging studies when patients are re-admitted [4][5][6]. Both Medical and surgical teams indulging on patient care could have simultaneous access to imaging studies on monitors throughout the hospital.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Compression of MR Images Using DWT by Comparing RGB and YCbCr Color Spaces

Jayprkash¹,

Vijay²

2013

JSIP

View full text Add to dashboard Cite

This paper consists of a lossy image compression algorithm dedicated to the medical images doing comparison of RGB and YCbCr color space. Several lossy/lossless transform coding techniques are used for medical image compression. Discrete Wavelet Transform (DWT) is one such widely used technique. After a preprocessing step (remove the mean and RGB to YCbCr transformation), the DWT is applied and followed by the bisection method including thresholding, the quantization, dequantization, the Inverse Discrete Wavelet Transform (IDWT), YCbCr to RGB transform of mean recovering. To obtain the best compression ratio (CR), the next step encoding algorithm is used for compressing the input medical image into three matrices and forward to DWT block a corresponding containing the maximum possible of run of zeros at its end. The last step decoding algorithm is used to decompress the image using IDWT that is applied to get three matrices of medical image.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Compression of MR Images Using DWT by Comparing RGB and YCbCr Color Spaces

Jayprkash¹,

Vijay²

2013

JSIP

View full text Add to dashboard Cite

show abstract

“…Then, only these important coefficients were transmitted instead of transmitting the entire image data, thereby achieving compression effect. Based on the curled DCT (Warped DCT, WDCT), Prabhu et al [20] proposed a 3D warped DCT (3D WDCT), by means of which a complete medical image compression scheme was presented. Bhavani and Thanushkodi [21] compared the performance of several fractal coding algorithms on MRI compression, including fractal coding standards, quasi-lossless fractal coding, and improved quasi-lossless fractal coding.…”

Section: B Non-roi Codingmentioning

confidence: 99%

A Fast Fractal Based Compression for MRI Images

et al. 2019

View full text Add to dashboard Cite

Magnetic resonance imaging (MRI), which assists doctors in determining clinical staging and expected surgical range, has high medical value. A large number of MRI images require a large amount of storage space and the transmission bandwidth of the PACS system in offline storage and remote diagnosis. Therefore, high-quality compression of MRI images is very research-oriented. Current compression methods for MRI images with high compression ratio cause loss of information on lesions, leading to misdiagnosis; compression methods for MRI images with low compression ratio does not achieve the desired effect. Therefore, a fast fractal-based compression algorithm for MRI images is proposed in this paper. First, three-dimensional (3D) MRI images are converted into a two-dimensional (2D) image sequence, which facilitates the image sequence based on the fractal compression method. Then, range and domain blocks are classified according to the inherent spatiotemporal similarity of 3D objects. By using self-similarity, the number of blocks in the matching pool is reduced to improve the matching speed of the proposed method. Finally, a residual compensation mechanism is introduced to achieve compression of MRI images with high decompression quality. The experimental results show that compression speed is improved by 2-3 times, and the PSNR is improved by nearly 10. It indicates the proposed algorithm is effective and solves the contradiction between high compression ratio and high quality of MRI medical images.

show abstract

“…The system proposed was helpful in satisfying the demands of patients by providing more and better medical services. Compression of images is one of the ways to reduce the storage space and bandwidth requirement [4].…”

Section: A Medical Imaging and Telemedicinementioning

confidence: 99%

Implementation of region based medical image compression for telemedicine application

Sophia

Anitha

2014

2014 IEEE International Conference on Computational Intelligence and Computing Research

View full text Add to dashboard Cite

There is an increasing demand for transmitting medical images for telemedicine application. These medical images are rich in radiological information and the file sizes associated with it are also large. Medical images such as MRI (Magnetic Resonance Imaging) produce human body pictures in digital form and they produce excessive amount of data. So compression is necessary for storage and transmission purpose. Image compression enhances the performance of any digital system by reducing the time and cost with or without reduction in image quality. The algorithms used in this paper utilize Region Of Interest (ROI) based compression which again increases the compression ratio compared to the traditional block based methods. The results of 3 different classical algorithms with and without ROI are compared and the results are reported. ROI is coded with good fidelity than NROI and also incorporates progressive transmission. Distortion rates and compression rates are evaluated for all images and the results are compared.

show abstract

3-D warped discrete cosine transform for MRI image compression

Cited by 22 publications

References 11 publications

Compression of MR Images Using DWT by Comparing RGB and YCbCr Color Spaces

Compression of MR Images Using DWT by Comparing RGB and YCbCr Color Spaces

A Fast Fractal Based Compression for MRI Images

Implementation of region based medical image compression for telemedicine application

Contact Info

Product

Resources

About