CARIC: A Novel Modeling of Combinatorial Approach for Radiological Image Compression

Lakshminarayana, M.; Sarvagya, Mrinal

doi:10.1007/978-3-319-57264-2_8

Cited by 1 publication

(1 citation statement)

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“…The proposed work is a continuation of our previous studies [18] [19][20] [21]. Where compression of medical image has been refined to get better compression performance.…”

Section: Proposed Techniquementioning

confidence: 92%

RM2 IC: Performance Analysis of Region based Mixed-mode Medical Image Compression

Lakshminarayana¹,

Sarvagya²

2017

IJIGSP

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Abstract-The medical data science has been changing from conventional analog to more powerful digital imaging systems for some time. These imagining systems produced images in digital form. As digital technology evolves and exceeds the capability of analog imaging devices, so too does the expansion in the range of applications for image guided surgical and diagnostic systems. The optimization of bandwidth and storage are the major issues in image processing technology. The Compressive Sensing (CS) algorithm can become prominent tool for these issues because it can sample the signal with much lesser sample rate than twice of the maximum frequency of the signal and reconstruct the signal similar to the original signal. This paper, presents a novel scheme Region based Mixed-mode Medical Image Compression (RM 2 IC). Here, the region of interest is compressed with lossless hybrid compression methods and the non-region of interest is com-pressed with lossy hybrid CS algorithm. RM 2 IC is compared with different existing hybrid compression methods and it outperforms better visual perceptional quality of reconstructed image and reduces the compression rate. The performance analysis is done based on PSNR, MSE and compression ratio.

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“…The proposed work is a continuation of our previous studies [18] [19][20] [21]. Where compression of medical image has been refined to get better compression performance.…”

Section: Proposed Techniquementioning

confidence: 92%