An efficient block based lossless compression of medical images

The proposed block-based lossless coding technique presented in this paper targets at compression of volumetric medical images of 8-bit and 16-bit depth. The novelty of the proposed technique lies in its ability of threshold selection for prediction and optimal block size for encoding. A resolution independent gradient edge detector is used along with the block adaptive arithmetic encoding algorithm with extensive experimental tests to find a universal threshold value and optimal block size independent of image resolution and modality. Performance of the proposed technique is demonstrated and compared with benchmark lossless compression algorithms. BPP values obtained from the proposed algorithm show that it is capable of effective reduction of inter-pixel and coding redundancy. In terms of coding efficiency, the proposed technique for volumetric medical images outperforms CALIC and JPEG-LS by 0.70 % and 4.62 %, respectively.

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A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images

International Journal of Healthcare Information Systems and Informatics ◽

10.4018/ijhisi.2020070104 ◽

2020 ◽

Vol 15 (3) ◽

pp. 65-81 ◽

Cited By ~ 1

Author(s):

Urvashi Sharma ◽

Meenakshi Sood ◽

Emjee Puthooran ◽

Yugal Kumar

Keyword(s):

Medical Images ◽

Predictive Coding ◽

Block Size ◽

Lossless Compression ◽

Threshold Values ◽

Efficient Coding ◽

Coding Efficiency ◽

Block Based ◽

Entropy Encoding ◽

Efficiency Rate

The digitization of human body, especially for treatment of diseases can generate a large volume of data. This generated medical data has a large resolution and bit depth. In the field of medical diagnosis, lossless compression techniques are widely adopted for the efficient archiving and transmission of medical images. This article presents an efficient coding solution based on a predictive coding technique. The proposed technique consists of Resolution Independent Gradient Edge Predictor16 (RIGED16) and Block Based Arithmetic Encoding (BAAE). The objective of this technique is to find universal threshold values for prediction and provide an optimum block size for encoding. The validity of the proposed technique is tested on some real images as well as standard images. The simulation results of the proposed technique are compared with some well-known and existing compression techniques. It is revealed that proposed technique gives a higher coding efficiency rate compared to other techniques.

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Absolutely Lossless Compression Of Medical Images

2005 IEEE Engineering in Medicine and Biology 27th Annual Conference ◽

10.1109/iembs.2005.1615340 ◽

2005 ◽

Cited By ~ 2

Author(s):

R. Ashraf ◽

M. Akbar

Keyword(s):

Medical Images ◽

Lossless Compression

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Lossless Compression of Medical Images by Content-Driven Laplacian Pyramid Splitting

Image Technology ◽

10.1007/978-3-642-58288-2_21 ◽

1996 ◽

pp. 595-611

Author(s):

B. Aiazzi ◽

L. Alparone ◽

S. Baronti

Keyword(s):

Medical Images ◽

Lossless Compression ◽

Laplacian Pyramid

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Analysis of Lossy and Lossless Compression Algorithms for Computed Tomography Medical Images Based on Bat and Simulated Annealing Optimization Techniques

Computational Intelligence Methods for Super-Resolution in Image Processing Applications ◽

10.1007/978-3-030-67921-7_6 ◽

2021 ◽

pp. 99-133

Author(s):

S. N. Kumar ◽

Ajay Kumar Haridhas ◽

A. Lenin Fred ◽

P. Sebastin Varghese

Keyword(s):

Computed Tomography ◽

Simulated Annealing ◽

Medical Images ◽

Lossless Compression ◽

Optimization Techniques ◽

Compression Algorithms

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Denoising Ultrasound Medical Images

Medical Imaging ◽

10.4018/978-1-5225-0571-6.ch031 ◽

2017 ◽

pp. 761-775

Author(s):

A.S.C.S. Sastry ◽

P.V.V. Kishore ◽

Ch. Raghava Prasad ◽

M.V.D. Prasad

Keyword(s):

Image Quality ◽

Medical Images ◽

Ultrasound Image ◽

Similarity Index ◽

Speckle Noise ◽

Ultrasound Images ◽

Medical Ultrasound ◽

Soft Thresholding ◽

Block Based

Medical ultrasound imaging has revolutioned the diagnostics of human body in the last few decades. The major drawback of ultrasound medical images is speckle noise. Speckle noise in ultrasound images is because of multiple reflections of ultrasound waves from hard tissues. Speckle noise degrades the medical ultrasound images lessening the visible quality of the image. The aim of this paper is to improve the image quality of ultrasound medical images by applying block based hard and soft thresholding on wavelet coefficients. Medical ultrasound image transformation to wavelet domain uses debauchee's mother wavelet. Divide the approximate and detailed coefficients into uniform blocks of size 8×8, 16×16, 32×32 and 64×64. Hard and soft thresholding on these blocks of approximate and detailed coefficients reduces speckle noise. Inverse transformation to original spatial domain produces a noise reduced ultrasound image. Experiments on medical ultrasound images obtained from diagnostic centers in Vijayawada, India show good improvements to ultrasound images visually. Quality of improved images in measured using peak signal to noise ratio (PSNR), image quality index (IQI), structural similarity index (SSIM).

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