ArticleEntropy (Basel, Switzerland)2022
Bendlet Transform Based Adaptive Denoising Method for Microsection Images.
Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 41 citations in OpenAlex.
- Enhancing clinical diagnostics: novel denoising methodology for brain MRI with adaptive masking and modified non-local block.Medical & biological engineering & computing · 2024Article
- A New X-ray Medical-Image-Enhancement Method Based on Multiscale Shannon-Cosine Wavelet.Entropy (Basel, Switzerland) · 2022Article
- Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets.Sensors (Basel, Switzerland) · 2022Article
- Anisotropic SpiralNet for 3D Shape Completion and Denoising.Sensors (Basel, Switzerland) · 2022Article
- Brain Tumor Segmentation Based on Bendlet Transform and Improved Chan-Vese Model.Entropy (Basel, Switzerland) · 2022Article
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
Abstract
Magnetic resonance imaging (MRI) plays an important role in disease diagnosis. The noise that appears in MRI images is commonly governed by a Rician distribution. The bendlets system is a second-order shearlet transform with bent elements. Thus, the bendlets system is a powerful tool with which to represent images with curve contours, such as the brain MRI images, sparsely. By means of the characteristic of bendlets, an adaptive denoising method for microsection images with Rician noise is proposed. In this method, the curve contour and texture can be identified as low-frequency components, which is not the case with other methods, such as the wavelet, shearlet, and so on. It is well known that the Rician noise belongs to a high-frequency channel, so it can be easily removed without blurring the clarity of the contour. Compared with other algorithms, such as the shearlet transform, block matching 3D, bilateral filtering, and Wiener filtering, the values of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) obtained by the proposed method are better than those of other methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.