Lossless Compression on MRI Images Using SWT

Anusuya, V.; Raghavan, Venkatesh; Kavitha, G.

doi:10.1007/s10278-014-9697-9

Cited by 16 publications

(3 citation statements)

References 15 publications

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“…4 , 6 , 8 , 10,11 Most of the analyzed papers indicated the need to develop more appropriate methodologies that include the overall costs for the telemedicine implementation versus the social costs of traditional medicine (cost of transferring a patient to a place with adequate technology to make “face-to-face” diagnosis or the cost of multiplying the health teams and the technical equipments). 12–39…”

Section: Discussionmentioning

confidence: 99%

National electrocardiographic mapping by telemedicine for diagnosis and prevention of cardiological pathologies in Paraguay

Galvañ

Rivas

Portillo

et al. 2019

Medicine Access @ Point of Care

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Introduction: Telemedicine tools offer multiple advantages to achieve an epidemiological screening of communities in rural settings countrywide. However, evidence on the cardiological pathology surveillance in these communities is limited. The feasibility of telemedicine as an electrocardiographic (EKG) mapping tool for the diagnosis and prevention of cardiological pathologies in Paraguay was investigated. Methods: A descriptive study was conducted in 60 telediagnostic centers countrywide in Paraguay to evaluate the feasibility of telemedicine as an EKG mapping tool for the diagnosis and prevention of cardiological pathologies over a period of 5 years from 2014 to 2018. The adherence rate was determined comparing yearly scheduled visits versus fulfilled visits at the telemedicine platform. Results: During the study, 246,217 remote EKG diagnoses were performed in 60 hospitals using telemedicine. The patients were 19.4% children/adolescents and 80.6% adults. The results of EKG tests in the children/adolescent group were 79.4% normal and 20.6% abnormal. The most frequent abnormal heart rhythms observed were sinusal bradicardia (10.6%), sinusal tachycardia (3.2%), and unspecified arrhythmia (2.8%). In the adult group, the results were 66.3% normal and 33.7% abnormal. The most frequent abnormal heart rhythms in this group were sinusal bradicardia (11.2%), blockade of the right branch (4.8%), and left ventricular hypertrophy (4.7%). The most frequent cardiovascular risk factors observed were the association of hypertension and obesity (40%), hypertension and diabetes (20%), and hypertension and dyslipidemia (19%). During the test period (2014-2018), the average rate of patient adherence to the prevention program was 2.26 for each 1000 diagnosis. Conclusion: These results demonstrate the feasibility of telemedicine as an EKG mapping tool for the diagnosis and prevention of cardiological pathologies in low-resource countries, thus enhancing cardiovascular disease surveillance and optimizing human and financial resources.

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Section: Discussionmentioning

confidence: 99%

National electrocardiographic mapping by telemedicine for diagnosis and prevention of cardiological pathologies in Paraguay

Galvañ

Rivas

Portillo

et al. 2019

Medicine Access @ Point of Care

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“…Anusuya et al [ 20 ] developed a new, lossless code employing a codec to reduce the size of 3D brain images. In this paper, MRI models are employed to analyze the effectiveness of the newly developed solution, and this paper focuses on sinking utilization time using parallel calculations.…”

Section: Introductionmentioning

confidence: 99%

Optimal Medical Image Size Reduction Model Creation Using Recurrent Neural Network and GenPSOWVQ

Sridhar¹,

Pareek²,

Kalidoss

et al. 2022

Journal of Healthcare Engineering

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Medical diagnosis is always a time and a sensitive approach to proper medical treatment. Automation systems have been developed to improve these issues. In the process of automation, images are processed and sent to the remote brain for processing and decision making. It is noted that the image is written for compaction to reduce processing and computational costs. Images require large storage and transmission resources to perform their operations. A good strategy for pictures compression can help minimize these requirements. The question of compressing data on accuracy is always a challenge. Therefore, to optimize imaging, it is necessary to reduce inconsistencies in medical imaging. So this document introduces a new image compression scheme called the GenPSOWVQ method that uses a recurrent neural network with wavelet VQ. The codebook is built using a combination of fragments and genetic algorithms. The newly developed image compression model attains precise compression while maintaining image accuracy with lower computational costs when encoding clinical images. The proposed method was tested using real-time medical imaging using PSNR, MSE, SSIM, NMSE, SNR, and CR indicators. Experimental results show that the proposed GenPSOWVQ method yields higher PSNR SSIMM values for a given compression ratio than the existing methods. In addition, the proposed GenPSOWVQ method yields lower values of MSE, RMSE, and SNR for a given compression ratio than the existing methods.

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“…Lossless coding methods are employed to retain the quality of an image in visual quality critical applications. Among the fields like remote sensing, business documentation, digital radiography, medical industry and satellite imagery, work is being done to achieve significant error-free compression [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

On the Utilization of Reversible Colour Transforms for Lossless 2-D Data Compression

Waleed

Khan

et al. 2020

Applied Sciences

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Reversible Colour Transforms (RCTs) in conjunction with Bi-level Burrows–Wheeler Compression Algorithm (BBWCA) allows for high-level lossless image compression as demonstrated in this study. The RCTs transformation results in exceedingly coordinated image information among the neighbouring pixels as compared to the RGB colour space. This aids the Burrows–Wheeler Transform (BWT) based compression scheme and achieves compression ratios of high degree at the subsequent steps of the program. Validation has been done by comparing the proposed scheme across a range of benchmarks schemes and the performance of the proposed scheme is above par the other schemes. The proposed compression outperforms the techniques exclusively developed for 2-D electrocardiogram (EEG), RASTER map and Color Filter Array (CFA) image compression. The proposed system shows no dependency over parameters like image size, its type or the medium in which it is captured. A comprehensive analysis of the proposed scheme concludes that it achieves a significant increase in compression and depicts comparable complexity similar to the various benchmark schemes.

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Lossless Compression on MRI Images Using SWT

Cited by 16 publications

References 15 publications

National electrocardiographic mapping by telemedicine for diagnosis and prevention of cardiological pathologies in Paraguay

National electrocardiographic mapping by telemedicine for diagnosis and prevention of cardiological pathologies in Paraguay

Optimal Medical Image Size Reduction Model Creation Using Recurrent Neural Network and GenPSOWVQ

On the Utilization of Reversible Colour Transforms for Lossless 2-D Data Compression

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