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Anne Gelb

Publications and source records attributed to Anne Gelb.

4 recordsLinked to original sources

Roughness models for particle adhesion.

The effects of different surface roughness models on a previously developed van der Waals adhesion model were examined. The van der Waals adhesion model represented surface roughness with a distribution of hemispherical asperities. It was found that the constraints used to define the asperity distribution on the surface, which were determined from AFM scans, varied with scan size and thus were not constant for all surfaces examined. The greatest variation in these parameters occurred with materials that had large asperities or with materials where a large fraction of the surface was covered by asperities. These rough surfaces were modeled with fractals and also with a fast Fourier transform algorithm. When the model surfaces generated using the Fourier transforms are used in the adhesion model, the model accurately predicts the experimentally observed adhesion forces measured with the AFM.

Journal Article↗

Improving the accuracy of volumetric segmentation using pre-processing boundary detection and image reconstruction.

The concentration edge -detection and Gegenbauer image-reconstruction methods were previously shown to improve the quality of segmentation in magnetic resonance imaging. In this study, these methods are utilized as a pre-processing step to the Weibull E-SD field segmentation. It is demonstrated that the combination of the concentration edge detection and Gegenbauer reconstruction method improves the accuracy of segmentation for the simulated test data and real magnetic resonance images used in this study.

Algorithms↗

Improving tissue segmentation of human brain MRI through preprocessing by the Gegenbauer reconstruction method.

The Gegenbauer image reconstruction method, previously shown to improve the quality of magnetic resonance images, is utilized in this study as a segmentation preprocessing step. It is demonstrated that, for all simulated and real magnetic resonance images used in this study, the Gegenbauer reconstruction method improves the accuracy of segmentation. Although it is more desirable to use the k-space data for the Gegenbauer reconstruction method, only information acquired from MR images is necessary for the reconstruction, making the procedure completely self-contained and viable for all human brain segmentation algorithms.

Algorithms↗

A method to reduce the Gibbs ringing artifact in MRI scans while keeping tissue boundary integrity.

Gibbs ringing is a well known artifact that effects reconstruction of images having discontinuities. This is a problem in the reconstruction of magnetic resonance imaging (MRI) data due to the many different tissues normally present in each scan. The Gibbs ringing artifact manifests itself at the boundaries of the tissues, making it difficult to determine the structure of the brain tissue. The Gegenbauer reconstruction method has been shown to effectively eliminate the effects of Gibbs ringing in other applications. This paper presents the application of the Gegenbauer reconstruction method to neuro-imaging.

Algorithms↗