Warren E. Smith

Correction of distortion in endoscope images

Images formed with endoscopes suffer from a spatial distortion due to the wide-angle nature of the endoscopes objective lens. This change in the size of objects with position precludes quantitative measurement of the area of the objects, which is important in endoscopy for accurately measuring ulcer and lesion sizes over time. A method for correcting the distortion characteristic of endoscope images is presented. A polynomial correction formula was developed for the endoscope lens and validated by comparing quantitative test areas before and after the distortion correction. The distortion correction has been incorporated into a computer program that could readily be applied to electronic images obtained at endoscopy using a desk-top computer. The research presented here is a key step towards the quantitative determination of the area of regions of interest in endoscopy.

Endoscopic measurement of lesion size: Improved accuracy with image processing

Endoscopic measurement of lesions is of great importance in the design and performance of clinical trials, as, for example, in studies of ulcer disease. Endoscopes are constructed with wide-angle lenses that significantly distort the image by creating a relative compression of points in its periphery. We have recently developed a computer program to correct the distortion of the wide-angle lens. We sought to determine the accuracy of the currently used open-biopsy forceps measurement technique and compare it to that of an image-processing technique designed to correct image distortion. The overall error of the open-biopsy forceps technique using an in vitro ulcer model was under-estimation of lesion size by 41.8% +/- 23.3%. When image processing was used to correct distortion, error was significantly decreased to 1.8% +/- 2.2% (p < 0.05). In vivo measurements were made using an inserted object of known size (coated chewing gum). The mean error of the forceps technique in vivo was 26.5% +/- 5.7% (under-estimation of size), which improved significantly to an error of 2.8% +/- 3.2% (p < 0.05) with the image-processing technique. We conclude that image processing significantly enhances the accuracy of measurement at endoscopy.

Linear estimation theory applied to the reconstruction of a 3-D vector current distribution

Linear estimation theory incorporating statistical a priori knowledge is applied to the inverse problem of reconstructing a static 3-D vector source field from another 3-D vector measurement field. The motivation for this development is to reconstruct 3-D electric current distributions from a set of magnetic measurements. Such a capability would be useful for the clinical determination of neural currents, for example. A simulation is presented to demonstrate the reconstruction of a class of simple nonbiological source objects, and to show the dependence of these reconstructions on the data taking configuration and the statistical a priori knowledge that is incorporated into the reconstruction process.

A LINEAR ESTIMATION APPROACH TO BIOMAGNETIC IMAGING

A reconstruction algorithm based on linear estimation theory in combination with Moore-Penrose pseudoinverse techniques is presented in order to image complex current distributions. Phantom experiments with current dipoles immersed in saline solution inside a glass phantom head and computer simulations demonstrate the applicability to biomagnetic imaging.

Estimation of the spatio-temporal correlations of biological electrical sources from their magnetic fields

A general formulation linking the spatial and temporal coherence of measurable magnetic fields with the corresponding spatial and temporal coherence of the inaccessible current sources is derived in the quasi-static model. A method for reconstructing the spatial and temporal coherence of the source distribution is presented. Such coherence maps would be useful descriptors of physiological processes occurring over time and space, and would represent more information than an image of the current sources frozen in time, or even a temporal sequence of such images.<<ETX>>

Effect of Z-motion in the phase of the K-space MRI data and identification of periodic Z-motion kernels

In 2-D spin-echo magnetic resonance imaging, patient motion perpendicular to the selected slice (out-of-plane motion) is difficult to detect. A novel method for detecting sinusoidal motion without using any special pulse sequences is proposed. Once the motion is detected, the artifacts arising from different sources may be substantially reduced, leading to better and more efficient diagnosis.<<ETX>>

Modeling data acquisition and the effects of patient motion in magnetic resonance imaging

In this paper, we present a comprehensive model for MR data acquisition in the presence of patient motion to provide a better understanding as to the source of motion artifacts. This model identifies and quantifies various sources of motion artifacts in 2-D Fourier imaging. We verify our model by comparing the results predicted by the model with actual MR images of phantoms subjected to motion with controlled parameters. We expect that the knowledge of the sources of artifacts will lead to new and better methods of compensating for them.

Modeling and correction of artifacts due to z-motion in 2-D MRI

In 2D Fourier magnetic resonance imaging (MRI), patient motion, including respiratory, cardiac, and involuntary motion, plays a significant role in degradation of the image quality. The in-plane motion (x-y motion) results only in phase distortions in the raw (Fourier domain) MRI data, which can be easily corrected once the motion kernel is known. However, the effect of motion in the slice-selection direction (z-motion) has not yet been completely analyzed due to its significantly more complex nature. The authors propose a novel model to represent the effect of z-motion in the data acquisition process, and then develop two postprocessing methods for the correction of z-motion artifacts provided that the z-motion kernel is known. The model takes the form of a multi-input single-output, shift-variant system. Thus, the inversion of this system is treated by using some nonlinear methods such as the projection onto convex sets (POCS) technique and a Monte Carlo method.<<ETX>>

Reconstruction of a Three-Dimensional Volume from a Motion-Corrupted Two-Dimensional Data Set in Magnetic Resonance Imaging

Patient motion plays an important role in the degradation of image quality in magnetic resonance imaging (MRI), in that ghost-like artifacts are produced in the final image that may obscure important features. The motion can be respiratory, cardiac, can involve blood flow, and can be voluntary or involuntary. The motion in the plane of the slice to be imaged introduces phase errors in the MRI signal that can be removed if the motion is known. Motion perpendicular to the slice, however, is more complicated because different structures move into and out of the slice. In this paper we present a model to connect the 3-D source to the final 2-D MRI data set, assuming that the source has a known, arbitrary motion in the direction perpendicular to the slice. We then discuss two different techniques to reconstruct the 3-D volume swept out by the slice during the data acquisition. Reconstructions are presented to demonstrate that 3-D information can indeed be extracted from the corrupted 2-D data set.

Correction of image-phase aberrations in MRI with applications

This paper presents a quick and efficient way to detect and correct the linear and constant image-phase terms associated with MR images. We show that this correction provides us with the knowledge of the exact location of the DC term in k-space, which proves to be useful in the detection of x and y motion parameters. In addition, by displaying the real positive part of the image after the proposed correction, we can reduce background noise, motion artifacts and flow artifacts. Examples, analyses and results are provided to demonstrate the usefulness of the proposed detection and correction method.