Visual enhancement of brain cancer MRI using multiscale dyadic filter and Hilbert transformation
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Ankit Vidyarthi
Abstract
The quality of the medical image plays a major role in decision making by the radiologists. There exists a visual differentiation between the normal scene color images and medical images. Due to the low illumination and unavailability of the color parameter, medical images require more attention by radiologists for decision making. In this paper a new approach is proposed that enhances the quality of the Magnetic Resonance (MR) images. Proposed approach uses the spectral information present in form of Amplitude and Frequency within the MR image slices for an enhancement. The extracted enhanced spectral information gives better visualization as compared with original signal image generated from MR scanner. The quantitative analysis of the proposed approach suggests that the new method is far better than the traditional state-of-art image enhancement methods.
Acknowledgment
The authors would like to thank all the individuals who provide their guidance in implementation of this work. Moreover, the author is highly appreciative towards Dr. Sunil Jakhar, Department of Radio Diagnosis, SMS Medical College Jaipur, Rajasthan, India for providing his precious time towards this work in providing data samples, validating the experimental results and other suggestions for improving this work.
Research Funding: The author states that there is no funding involved with this work.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Conflict of Interest: The author states that there exists no conflict of interest.
Informed Consent: Informed consent has been obtained from all individuals included in this study.
Ethical Approval: The research related to human use complied with all the relevant national regulations and institutional policies and was performed in accordance with the tenets of the Helsinki declaration, and has been approved by the authors’ institutional review board.
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Nonlinear analysis of scalp EEGs from normal and brain tumour subjects
- Dimensionality reduction for EEG-based sleep stage detection: comparison of autoencoders, principal component analysis and factor analysis
- EEG signal classification based on SVM with improved squirrel search algorithm
- The effect of attentional focusing strategies on EMG-based classification
- Identification of dental pain sensation based on cardiorespiratory signals
- ScatT-LOOP: scattering tetrolet-LOOP descriptor and optimized NN for iris recognition at-a-distance
- A detailed and comparative work for retinal vessel segmentation based on the most effective heuristic approaches
- Visual enhancement of brain cancer MRI using multiscale dyadic filter and Hilbert transformation
- Raspberry Pi implemented with MATLAB simulation and communication of physiological signal-based fast chaff point (RPSC) generation algorithm for WBAN systems
- Short Communication
- How yarn orientation limits fibrotic tissue ingrowth in a woven polyester heart valve scaffold: a case report
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Nonlinear analysis of scalp EEGs from normal and brain tumour subjects
- Dimensionality reduction for EEG-based sleep stage detection: comparison of autoencoders, principal component analysis and factor analysis
- EEG signal classification based on SVM with improved squirrel search algorithm
- The effect of attentional focusing strategies on EMG-based classification
- Identification of dental pain sensation based on cardiorespiratory signals
- ScatT-LOOP: scattering tetrolet-LOOP descriptor and optimized NN for iris recognition at-a-distance
- A detailed and comparative work for retinal vessel segmentation based on the most effective heuristic approaches
- Visual enhancement of brain cancer MRI using multiscale dyadic filter and Hilbert transformation
- Raspberry Pi implemented with MATLAB simulation and communication of physiological signal-based fast chaff point (RPSC) generation algorithm for WBAN systems
- Short Communication
- How yarn orientation limits fibrotic tissue ingrowth in a woven polyester heart valve scaffold: a case report
