Gerald Jesion

Microscopic Imaging of Porous Media With X-Ray Computer Tomography

This paper presents a new method for imaging the 3D microstructure of porous media. The method is based on high-resolution X-ray computer tomography (CT) where a cone-shaped, diverging X-ray beam is used to generate 2D transmission images. Unlike traditional X-ray CT, a 3D reconstruction array is created directly instead of creating a series of 2D slices. This allows direct measurement of 3D geometric and topologic properties of porous media on a microscale. The authors results also demonstrate the effectiveness of the high-resolution system for imaging the distribution of two fluid phases in the void space. The imaging system overcomes the limitations of current methods and has enormous potential for quantifying the microstructure of chaotic porous media.

FTIR: fundamentals and applications in the analysis of dilute vehicle exhaust

FTIR spectroscopy has been shown to be a valuable tool in the analysis of complex gas phase mixtures, such a dilute vehicle exhaust. Regulated and non-regulated vehicle emissions have been routinely sampled and analyzed using prototype instrumentation developed in this laboratory, and in several other laboratories over the last decade. More recently, commercial versions of these FTIR analyzers have become available through several manufacturers. This paper reviews the data acquisition and processing techniques utilized by the FTIR analyzer developed in this laboratory. The statistical detection limits for 22 of the components analyzed by the system are presented. In addition, the linearity of the carbon monoxide (CO) analysis is demonstrated over several orders of magnitude. Experiments designed to study the effects of environmental parameters on the accuracy and the sensitivity of the system are also described.

Fundamental Aspects of micro-CT in Cone-Beam Geometry

The terms “micro-CT” and “microtomography” have been used recently to describe the extension of the techniques of computed tomography to the evaluation of objects and structures where the dimensions of structures of interest are measured in micrometers or tens of micrometers. The resolution thus implied is not microscopic in the sense of a traditional microscope but still is much smaller than that approached by the vast majority of computed tomography systems.

Neural network classifier to threshold images from 3D microcomputed tomography

Summary form only given. The authors discuss the use of a neural network to perform context-dependent thresholding of gray-scale three-dimensional images of trabecular and cortical bone as measured in vitro by high-resolution X-ray computed tomography. A classifier is constructed on the basis of a simple model of the blurring necessarily associated with the tomographic measurement.<<ETX>>