Theoretical Foundations of Anisotropic Diffusion in Image Processing

We describe a chain of algorithms for molecular surface and volumetric mesh generation. We take as inputs the centers and radii of all atoms of a molecule and the toolchain outputs both triangular and tetrahedral meshes that can be used for molecular shape modeling and simulation. Experiments on a number of molecules are demonstrated, showing that our methods possess several desirable properties: feature-preservation, local adaptivity, high quality, and smoothness (for surface meshes). We also demonstrate an example of molecular simulation using the finite element method and the meshes generated by our method. The approaches presented and their implementations are also applicable to other types of inputs such as 3D scalar volumes and triangular surface meshes with low quality, and hence can be used for generation/improvment of meshes in a broad range of applications.

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“…To characterize the important features on a surface mesh, we compute so-called local structure tensor [21,45,50,51] as follows:…”

Section: Surface Mesh Quality Improvementmentioning

confidence: 99%

Feature-preserving adaptive mesh generation for molecular shape modeling and simulation

Holst

McCammon

2008

Journal of Molecular Graphics and Modelling

106

122

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“…In general, the tensor can be built in many ways. In this work, either CoherenceEnhancing Diffusion (CED) for enhancing line-like textures in the image or Edge-Enhancing Diffusion (EED) to reduce the noise while enhancing edges is used [40,41]. In this paper, a hybrid diffusion filter with a Continuous Switch (HDCS) has been used, combining the CED and EED algorithms [40].…”

Section: Preprocessing Stagementioning

confidence: 99%

“…In this paper, three schemes have been investigated. These are the standard discretization scheme [46], the nonnegative discretization scheme [47] and the optimized scheme [42]. Fig.4 (a) and (b) show the stencil representations of the standard discretization and the non-negative discretization for assuming that the pixels have length 1 in both directions.…”

Section: Diffusion Schemesmentioning

confidence: 99%

A fully automatic nerve segmentation and morphometric parameter quantification system for early diagnosis of diabetic neuropathy in corneal images

Al-Fahdawi

Qahwaji

Al-Waisy

et al. 2016

Computer Methods and Programs in Biomedicine

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“…Real anisotropic behaviour is possible when a diffusion tensor is used. As a prototype for nonlinear anisotropic diffusion filtering edge-enhancing diffusion (EED) [17] is considered and the idea is to reduce smoothing across edges while still permitting diffusion along them. The elliptic differential operator for EED diffusion is governed by…”

Section: Specific Smoothing Operatorsmentioning

confidence: 99%

Image compression with B-tree coding algorithm enhanced by data modelling with Burrows-Wheeler transformation

2016

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Theoretical Foundations of Anisotropic Diffusion in Image Processing

Cited by 1,048 publications

References 16 publications

Feature-preserving adaptive mesh generation for molecular shape modeling and simulation

Feature-preserving adaptive mesh generation for molecular shape modeling and simulation

A fully automatic nerve segmentation and morphometric parameter quantification system for early diagnosis of diabetic neuropathy in corneal images

Image compression with B-tree coding algorithm enhanced by data modelling with Burrows-Wheeler transformation

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