Enhancement of brain tumor images

Viswanath, K.; Shweta, .

doi:10.1109/rteict.2017.8256926

Cited by 9 publications

(6 citation statements)

References 9 publications

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“…©IJRASET (UGC Approved Journal): All Rights are Reserved [4], (e) TW-CES-LAB space our result (f) TW-CES-LAB with our proposed Fusion.…”

Section: A) B)mentioning

confidence: 74%

“…Jaspreet et al [8] have proposed an novel method of image enhancement using the scaling of DC and AC coefficients in CT domain for colour image enhancement. Kapinaiah et al [4] have proposed the DC coefficient scaling in DCT transform domain along with the power transformation to enhance the medical images of Brain Tumors. Although the method is efficient but still scope of improvement is there.…”

Section: A Review Of Contrast Enhancement Methodsmentioning

confidence: 99%

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Content Preserving Medical Image Enhancement by DC Coefficients Scaling in LAB-DCT Domain

Jarholiya¹

2018

IJRASET

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Medical images are acquired from different modalities thus captured medical images usually suffers from noise low contrast and medical images are used for the human health monitoring and disease diagnosis thus it is essential to improve the contrast for the better image quality before being analysed and diagnosed. In this paper to preserve the colour content a modified method of DC coefficient scaling in the compressed DCT domain is proposed to enhance the contrast of the images. For colour preservation, it is proposed to implement DC coefficient scaling in the CIE-Lab colour space. The contrast is only enhanced using the L component and chrominance information is preserved. This improves the entropy over the standard DC coefficient scaling method. The performance of three methods is compared based on SNR, absolute standard deviation difference (ASDD) and entropy analysis. Based on entropy analysis the order of the Twicing function is varied for better DC coefficient enhancement. The methods are tested on various medical images from different environment.

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“…©IJRASET (UGC Approved Journal): All Rights are Reserved [4], (e) TW-CES-LAB space our result (f) TW-CES-LAB with our proposed Fusion.…”

Section: A) B)mentioning

confidence: 74%

Section: A Review Of Contrast Enhancement Methodsmentioning

confidence: 99%

Content Preserving Medical Image Enhancement by DC Coefficients Scaling in LAB-DCT Domain

Jarholiya¹

2018

IJRASET

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“…Kaur and Rani [27] recommended CLAHE after comparing their results with the other histogram equalization methods for image enhancement. Viswanath [28] proposed a combination of color enhancement by scaling and power-law transformations. They adjusted local background illumination, and then they applied power law transformation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A higher value shows the better quality of the enhanced image. SRSIM between two images is defined as: 𝑆𝑅𝑆𝐼𝑀 = ∑ 𝑆 𝐿 (𝑥) 𝑥∈∆ 𝑅 𝑚 (𝑥) ∑ 𝑅 𝑚 (𝑥) 𝑥∈∆ (28) where, Δ means the entire image special domain, SL (x) is the similarity, and Rm(x) is the weight importance of 𝑆 𝐿 (𝑥) . SRSIM value is improved in the proposed method and approaches the maximum value that is one.…”

Section: Riesz Transformed Based Feature Similarity Index Metric (Rfsim)mentioning

confidence: 99%

An Approach for Enhancement of MR Images of Brain Tumor

Mishra¹,

Kaur²

2022

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Magnetic Resonance Imaging plays an important role in diagnosing the brain tumor accurately, but it requires the approach to enhance the magnetic resonance images to assist physicians in brain tumor detection and making the treatment plan precisely to reduce the mortality rate. Therefore, in this proposed work, a comprehensive learning-based elephant herding optimization technique has been introduced to select the optimal value of smoothness factor in Bi-Histogram Equalization with Adaptive Sigmoid Function that enhances the visual quality as well as the appearance of the suspicious regions in magnetic resonance images. Further, the enhancement performance has been evaluated by the enhancement quality metrics. The metrics used include mean square error, peak signal to noise ratio, mean absolute error, structural similarity index metric, feature similarity index metric, Riesz transformed based feature similarity index metric, spectral residual-based similarity index metric, and absolute mean brightness error. The outcomes of this proposed work have a remarkable impact on enhancing magnetic resonance images and providing visual assistance for diagnosing brain tumors. The performance of the evaluation metrics is verified with Friedman's mean rank test, which strongly indicates a statistical difference between the proposed method and state-of-the-art methods.

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“…It focused on the full cycles of the big data processing, which includes medical big data preprocessing, big data tools and algorithms, big data visualization, and security issues in big data. Viswanath and Shweta[16] focused on the enhancement of medical brain tumor images in the spatial domain as well as transform domain. In the spatial domain, power law transformation is adopted and in the transform domain, color enhancement by scaling the DCT coefficients has been used.…”

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confidence: 99%

An Empirical Study on Some Image Enhancement Techniques towards Identification of Chronical Diseases

Puli¹,

James²

2020

IJCA

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Detection and analysis in medical images, image enhancement techniques are one of the most important phases. The main aim of Image enhancement is to produce with suitable image and representation of the transformed image. These enhanced medical images can be used identification of chronical diseases. A lot of work has been done by different researchers and scientists in the field of image enhancement in the recent past. This paper discusses previous research work about the some image enhancement techniques towards identification of chronical diseases and tried to find the most suitable and appropriate image enhancement techniques identification of chronical diseases.

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Enhancement of brain tumor images

Cited by 9 publications

References 9 publications

Content Preserving Medical Image Enhancement by DC Coefficients Scaling in LAB-DCT Domain

Content Preserving Medical Image Enhancement by DC Coefficients Scaling in LAB-DCT Domain

An Approach for Enhancement of MR Images of Brain Tumor

An Empirical Study on Some Image Enhancement Techniques towards Identification of Chronical Diseases

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