Journal ArticleDOI
A review on CT image noise and its denoising
Manoj Diwakar,Manoj Kumar +1 more
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TLDR
A brief introduction about CT imaging, the characteristics of noise in CT images and the popular methods of CT image denoising are presented and the merits and drawbacks of CT Image Denoising methods are discussed.About:
This article is published in Biomedical Signal Processing and Control.The article was published on 2018-04-01. It has received 222 citations till now. The article focuses on the topics: Image noise & Iterative reconstruction.read more
Citations
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Journal ArticleDOI
Brief review of image denoising techniques
TL;DR: This paper gives the formulation of the image denoising problem, and then it presents several imageDenoising techniques, which discuss the characteristics of these techniques and provide several promising directions for future research.
Journal ArticleDOI
Image denoising review: From classical to state-of-the-art approaches
TL;DR: This article focuses on classifying and comparing some of the significant works in the field of denoising and explains why some methods work optimally and others tend to create artefacts and remove fine structural details under general conditions.
Journal ArticleDOI
Advances in Orthotic and Prosthetic Manufacturing: A Technology Review.
Jorge Barrios-Muriel,Francisco Romero-Sánchez,Francisco Javier Alonso-Sánchez,David Rodríguez Salgado +3 more
TL;DR: Different methodologies for additive manufacturing along with the principal methods for collecting 3D body shapes and their application in the manufacturing of functional devices for rehabilitation purposes such as splints, ankle-foot orthoses, or arm prostheses are analysed.
Journal ArticleDOI
Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation.
TL;DR: The proposed SBBS-CNN provides an accurate and effective tool for automated liver segmentation and showed superior performance in comparison with state-of-art methods, including U-Net, pixel-based CNN, active contour, level-sets and graph-cut algorithms.
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Methods for image denoising using convolutional neural network: a review
TL;DR: An elaborate study on different CNN techniques used in image denoising with CNN, where some state-of-the-arts CNN image Denoising methods were depicted in graphical forms, while other methods were elaborately explained.
References
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Journal ArticleDOI
Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Journal ArticleDOI
Nonlinear total variation based noise removal algorithms
TL;DR: In this article, a constrained optimization type of numerical algorithm for removing noise from images is presented, where the total variation of the image is minimized subject to constraints involving the statistics of the noise.
Journal ArticleDOI
Scale-space and edge detection using anisotropic diffusion
Pietro Perona,Jitendra Malik +1 more
TL;DR: A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced, chosen to vary spatially in such a way as to encourage intra Region smoothing rather than interregion smoothing.
Proceedings ArticleDOI
Bilateral filtering for gray and color images
Carlo Tomasi,Roberto Manduchi +1 more
TL;DR: In contrast with filters that operate on the three bands of a color image separately, a bilateral filter can enforce the perceptual metric underlying the CIE-Lab color space, and smooth colors and preserve edges in a way that is tuned to human perception.