Image Distortion Types Research Articles

Quantitative comparison and evaluation of two commercially available, two-dimensional electrophoresis image analysis software packages, Z3 and Melanie

While a variety of software packages are available for analyzing two-dimensional electrophoresis (2-DE) gel images, no comparisons between these packages have been published, making it difficult for end users to determine which package would best meet their needs. The goal here was to develop a set of tests to quantitatively evaluate and then compare two software packages, Melanie 3.0 and Z3, in three of the fundamental steps involved in 2-DE image analysis: (i) spot detection, (ii) gel matching, and (iii) spot quantitation. To test spot detection capability, automatically detected protein spots were compared to manually counted, "real" protein spots. Spot matching efficiency was determined by comparing distorted (both geometrically and nongeometrically) gel images with undistorted original images, and quantitation tests were performed on artificial gels with spots of varying Gaussian volumes. In spot detection tests, Z3 performed better than Melanie 3.0 and required minimal user intervention to detect approximately 89% of the actual protein spots and relatively few extraneous spots. Results from gel matching tests depended on the type of image distortion used. For geometric distortions, Z3 performed better than Melanie 3.0, matching 99% of the spots, even for extreme distortions. For nongeometrical distortions, both Z3 and Melanie 3.0 required user intervention and performed comparably, matching 95% of the spots. In spot quantitation tests, both Z3 and Melanie 3.0 predicted spot volumes relatively well for spot ratios less than 1:6. For higher ratios, Melanie 3.0 did much better. In summary, results suggest Z3 requires less user intervention than Melanie 3.0, thus simplifying differential comparison of 2-DE gel images. Melanie 3.0, however, offers many more optional tools for image editing, spot detection, data reporting and statistical analysis than Z3. All image files used for these tests and updated information on the software are available on the internet (http://www.umbc.edu/proteome), allowing similar testing of other 2-DE image analysis software packages.

A universal image quality index

We propose a new universal objective image quality index, which is easy to calculate and applicable to various image processing applications. Instead of using traditional error summation methods, the proposed index is designed by modeling any image distortion as a combination of three factors: loss of correlation, luminance distortion, and contrast distortion. Although the new index is mathematically defined and no human visual system model is explicitly employed, our experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error. Demonstrative images and an efficient MATLAB implementation of the algorithm are available online at http://anchovy.ece.utexas.edu//spl sim/zwang/research/quality_index/demo.html.

Reliability analysis of the rank transform for stereo matching

The rank transform is a nonparametric technique which has been recently proposed for the stereo matching problem. The motivation behind its application to this problem is its invariance to certain types of image distortion and noise, as well as its amenability to real-time implementation. This paper derives one constraint which must be satisfied for a correct match. This has been termed the rank constraint. Experimental work has shown that this constraint is capable of resolving ambiguous matches, thereby improving matching reliability. A novel matching algorithm incorporating the rank constraint has also been proposed. This modified algorithm consistently resulted in an increased percentage of correct matches, for all test imagery used. Furthermore, the rank constraint has been used to devise a method of identifying regions of an image where the rank transform, and hence matching outcome, is more susceptible to noise. Experimental results have shown that the errors predicted using this technique are consistent with the actual errors which result when images are corrupted with noise. Such a method could be used to identify matches which are likely to be incorrect and/or provide a measure of confidence in a match.

Differential Image Distortion Correction

AbstractImaging techniques often suffer from distortion effects. Former methods of reducing these distortions have been based either on improving the imaging technique (i.e., to avoid distortions) or on the use of reference samples (i.e., to determine the distortion field by imaging of a known structure. We present a novel method of correcting image distortion by evaluating the imaged position changes due to two small sample position shifts. The algorithm allows us to calculate a vector field, which enables us to determine the “undistorted” position of any point of the image. The presented method has very low presuppositions about the sample, requires no reference samples, and is applicable to any type of image distortion. In addition to the presentation of the method's theoretical basis and a description of the computational method, we present corrected secondary ion mass spectroscopy (SIMS) images of a regular structure (a copper grid) as well as a stochastic distribution (sodium impurities) to show the results of empirical data.

Differential Image Distortion Correction

Imaging techniques often suffer from distortion effects. Former methods of reducing these distortions have been based either on improving the imaging technique (i.e., to avoid distortions) or on the use of reference samples (i.e., to determine the distortion field by imaging of a known structure. We present a novel method of correcting image distortion by evaluating the imaged position changes due to two small sample position shifts. The algorithm allows us to calculate a vector field, which enables us to determine the "undistorted" position of any point of the image. The presented method has very low presuppositions about the sample, requires no reference samples, and is applicable to any type of image distortion. In addition to the presentation of the method's theoretical basis and a description of the computational method, we present corrected secondary ion mass spectroscopy (SIMS) images of a regular structure (a copper grid) as well as a stochastic distribution (sodium impurities) to show the results of empirical data.

An Unexpected Cause of Magnetic Resonance Image Distortion

(Grady) Fellow.(Perkins) Assistant Professor.Received from the Department of Anesthesiology, Mayo Clinic, Rochester, Minnesota. Submitted for publication April 5, 1996. Accepted for publication December 18, 1996.Address reprint requests to Dr. Perkins: Department of Anesthesiology, Mayo Clinic, 200 First Street, SW, Rochester, Minnesota 55905.Anesthesia services in the magnetic resonance imaging (MRI) suite are increasing and require that the anesthetic equipment used is adequate to ensure patient safety, is MRI compatible, and has a negligible effect on image quality. We report a case in which the MRI scan quality was noticeably degraded by an unsuspected but commonly used piece of anesthesia equipment, the pilot balloon valve of a conventional endotracheal tube.A 17-yr-old trauma patient with a known L4burst fracture required general anesthesia for a detailed MR examination of the spine and paraspinous region. After successful induction of general anesthesia, the patient's trachea was intubated with a 7.0 cuffed endotracheal tube (Lo-Pro; Mallinkrodt Medical, St. Louis, MO). The initial T2-weighted, gradient recalled MR examination revealed gross image degradation in the sagittal and transverse sections of the cervical spine region. The image artifact was consistent with ferromagnetic interference. A search for a source of ferromagnetic interference was initially unsuccessful. A radiology technician reported that similar interference had been observed in the past and was related to the position of the pilot balloon. Repositioning the pilot balloon 5 cm away from the surface of the neck area eliminated the distortion in a repeated MR scan. Subsequent inspection of the pilot balloon revealed a ferromagnetic spring that closes the pilot balloon valve.The strength of the magnetic field and the nature of the signal needed to generate the image requires that the anesthesiologist use nonferromagnetic materials in the MRI suite. It has long been known that ferromagnetic materials can interfere with the magnetic field generated by the MRI scanner. [1,2]This case illustrates how even a very small ferromagnetic object can severely distort a magnetic resonance image in an adult patient. Brenn and Saldutti [3] reported a similar episode of ferromagnetic interference during an MRI scan in a 6-month-old infant. The larger body size of the adult and the greater distance from the skin and pilot balloon to the internal structures to be examined does not appear to offer any significant protection of MRI quality. Pilot balloon springs of oral RAE tubes and laryngeal mask airways have also been implicated in MRI degradation. [4,5] The spring within the pilot balloon valve apparatus (Bespak PVC Medical Check Valve, Tenax Corporation, Apex, NC) is made of stainless steel and causes the image distortion. Image degradation only occurs when the pilot balloon valve containing this spring lies directly on the area of the head or neck to be scanned (Figure 1). According to the manufacturer (Tenax Corporation), this spring is present in all biomedical pilot balloon valves. Although plastic versions have been used in the past, the spring is best made of stainless steel because of its small size and the need for highly reliable operation. The risk for direct patient injury via induced heat production or dislocation of the valve spring is insignificant. The type of image distortion described by this report is easily avoided by placing the pilot balloon as far from the area to be examined as possible. We have found it convenient to secure the pilot balloon near the y-connector of the anesthesia circuit, thereby separating the pilot balloon from the skin surface by at least 3 cm and preventing image distortion.