Combined T2 -preparation and two-dimensional pencil-beam inner volume selection.

PURPOSE: To improve coronary magnetic resonance angiography (MRA) by combining a two-dimensional (2D) spatially selective radiofrequency (RF) pulse with a T2 -preparation module ("2D-T2 -Prep"). METHODS: An adiabatic T2 -Prep was modified so that the first and last pulses were of differing spatial selectivity. The first RF pulse was replaced by a 2D pulse, such that a pencil-beam volume is excited. The last RF pulse remains nonselective, thus restoring the T2 -prepared pencil-beam, while tipping the (formerly longitudinal) magnetization outside of the pencil-beam into the transverse plane, where it is then spoiled. Thus, only a cylinder of T2 -prepared tissue remains for imaging. Numerical simulations were followed by phantom validation and in vivo coronary MRA, where the technique was quantitatively evaluated. Reduced field-of-view (rFoV) images were similarly studied. RESULTS: In vivo, full field-of-view 2D-T2 -Prep significantly improved vessel sharpness as compared to conventional T2 -Prep, without adversely affecting signal-to-noise (SNR) or contrast-to-noise ratios (CNR). It also reduced respiratory motion artifacts. In rFoV images, the SNR, CNR, and vessel sharpness decreased, although scan time reduction was 60%. CONCLUSION: When compared with conventional T2 -Prep, the 2D-T2 -Prep improves vessel sharpness and decreases respiratory ghosting while preserving both SNR and CNR. It may also acquire rFoV images for accelerated data acquisition.

Validation of a computer-assisted system on classifying lower third molars

Objectives: The present study evaluates the reliability of the Radio Memory® software (Radio Memory; Belo Horizonte,Brasil.) on classifying lower third molars, analyzing intra- and interexaminer agreement of the results. Study Design: An observational, descriptive study of 280 lower third molars was made. The corresponding orthopantomographs were analyzed by two examiners using the Radio Memory® software. The exam was repeated 30 days after the first observation by each examiner. Both intra- and interexaminer agreement were determined using the SPSS v 12.0 software package for Windows (SPSS; Chicago, USA). Results: Intra- and interexaminer agreement was shown for both the Pell & Gregory and the Winter classifications, p<0.01, with 99% significant correlation between variables in all the cases. Conclusions: The use of Radio Memory® software for the classification of lower third molars is shown to be a valid alternative to the conventional method (direct evaluation on the orthopantomograph), for both clinical and investigational applications.

Image processing of false identity documents for forensic intelligence

Forensic intelligence has recently gathered increasing attention as a potential expansion of forensic science that may contribute in a wider policing and security context. Whilst the new avenue is certainly promising, relatively few attempts to incorporate models, methods and techniques into practical projects are reported. This work reports a practical application of a generalised and transversal framework for developing forensic intelligence processes referred to here as the Transversal model adapted from previous work. Visual features present in the images of four datasets of false identity documents were systematically profiled and compared using image processing for the detection of a series of modus operandi (M.O.) actions. The nature of these series and their relation to the notion of common source was evaluated with respect to alternative known information and inferences drawn regarding respective crime systems. 439 documents seized by police and border guard authorities across 10 jurisdictions in Switzerland with known and unknown source level links formed the datasets for this study. Training sets were developed based on both known source level data, and visually supported relationships. Performance was evaluated through the use of intra-variability and inter-variability scores drawn from over 48,000 comparisons. The optimised method exhibited significant sensitivity combined with strong specificity and demonstrates its ability to support forensic intelligence efforts.

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is oftenassociated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcificationsis performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcificationshave been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the senseof adding new features not only related to the shape

Detection of beetle damage in forests by X-ray CT image processing

Some beetle species can have devastating economic impacts on forest and nursery industries. A recent example is Anophophora glabripennis, a species of beetle known in the United States as the ''Asian Longhorrned beetle'', which has damaged many American forests, and is a threat which can unintentionally reach south American countries, including Brazil. This work presents a new method based on X-ray computerized tomography (CT) and image processing for beetle injury detection in forests. Its results show a set of images with correct identification of the location of beetles in living trees as well as damage evaluation with time.

The Shadow Moiré method using the phase shifting technique and digital image processing: computational implementation and application to the 3D-reconstruction of a buckled plate

The Shadow Moiré fringe patterns are level lines of equal depth generated by interference between a master grid and its shadow projected on the surface. In simplistic approach, the minimum error is about the order of the master grid pitch, that is, always larger than 0,1 mm, resulting in an experimental technique of low precision. The use of a phase shift increases the accuracy of the Shadow Moiré technique. The current work uses the phase shifting method to determine the surfaces three-dimensional shape using isothamic fringe patterns and digital image processing. The current study presents the method and applies it to images obtained by simulation for error evaluation, as well as to a buckled plate, obtaining excellent results. The method hands itself particularly useful to decrease the errors in the interpretation of the Moiré fringes that can adversely affect the calculations of displacements in pieces containing many concave and convex regions in relatively small areas.

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.

Spectral retinal image processing and analysis for ophthalmology

Diabetic retinopathy, age-related macular degeneration and glaucoma are the leading causes of blindness worldwide. Automatic methods for diagnosis exist, but their performance is limited by the quality of the data. Spectral retinal images provide a significantly better representation of the colour information than common grayscale or red-green-blue retinal imaging, having the potential to improve the performance of automatic diagnosis methods. This work studies the image processing techniques required for composing spectral retinal images with accurate reflection spectra, including wavelength channel image registration, spectral and spatial calibration, illumination correction, and the estimation of depth information from image disparities. The composition of a spectral retinal image database of patients with diabetic retinopathy is described. The database includes gold standards for a number of pathologies and retinal structures, marked by two expert ophthalmologists. The diagnostic applications of the reflectance spectra are studied using supervised classifiers for lesion detection. In addition, inversion of a model of light transport is used to estimate histological parameters from the reflectance spectra. Experimental results suggest that the methods for composing, calibrating and postprocessing spectral images presented in this work can be used to improve the quality of the spectral data. The experiments on the direct and indirect use of the data show the diagnostic potential of spectral retinal data over standard retinal images. The use of spectral data could improve automatic and semi-automated diagnostics for the screening of retinal diseases, for the quantitative detection of retinal changes for follow-up, clinically relevant end-points for clinical studies and development of new therapeutic modalities.

Problem solving and computer-assisted instruction in science education : analysis of research findings and the research process /

The quantitative component of this study examined the effect of computerassisted instruction (CAI) on science problem-solving performance, as well as the significance of logical reasoning ability to this relationship. I had the dual role of researcher and teacher, as I conducted the study with 84 grade seven students to whom I simultaneously taught science on a rotary-basis. A two-treatment research design using this sample of convenience allowed for a comparison between the problem-solving performance of a CAI treatment group (n = 46) versus a laboratory-based control group (n = 38). Science problem-solving performance was measured by a pretest and posttest that I developed for this study. The validity of these tests was addressed through critical discussions with faculty members, colleagues, as well as through feedback gained in a pilot study. High reliability was revealed between the pretest and the posttest; in this way, students who tended to score high on the pretest also tended to score high on the posttest. Interrater reliability was found to be high for 30 randomly-selected test responses which were scored independently by two raters (i.e., myself and my faculty advisor). Results indicated that the form of computer-assisted instruction (CAI) used in this study did not significantly improve students' problem-solving performance. Logical reasoning ability was measured by an abbreviated version of the Group Assessment of Lx)gical Thinking (GALT). Logical reasoning ability was found to be correlated to problem-solving performance in that, students with high logical reasoning ability tended to do better on the problem-solving tests and vice versa. However, no significant difference was observed in problem-solving improvement, in the laboratory-based instruction group versus the CAI group, for students varying in level of logical reasoning ability.Insignificant trends were noted in results obtained from students of high logical reasoning ability, but require further study. It was acknowledged that conclusions drawn from the quantitative component of this study were limited, as further modifications of the tests were recommended, as well as the use of a larger sample size. The purpose of the qualitative component of the study was to provide a detailed description ofmy thesis research process as a Brock University Master of Education student. My research journal notes served as the data base for open coding analysis. This analysis revealed six main themes which best described my research experience: research interests, practical considerations, research design, research analysis, development of the problem-solving tests, and scoring scheme development. These important areas ofmy thesis research experience were recounted in the form of a personal narrative. It was noted that the research process was a form of problem solving in itself, as I made use of several problem-solving strategies to achieve desired thesis outcomes.

A comparison of two computer-assisted remedial reading programs for adolescent unskilled readers : component reading skills and repeated reading

This study compared the relative effectiveness of two computerized remedial reading programs in improving the reading word recognition, rate, and comprehension of adolescent readers demonstrating significant and longstanding reading difficulties. One of the programs involved was Autoskill Component Reading Subskills Program, which provides instruction in isolated letters, syllables, and words, to a point of rapid automatic responding. This program also incorporates reading disability subtypes in its approach. The second program, Read It Again. Sam, delivers a repeated reading strategy. The study also examined the feasibility of using peer tutors in association with these two programs. Grade 9 students at a secondary vocational school who satisfied specific criteria with respect to cognitive and reading ability participated. Eighteen students were randomly assigned to three matched groups, based on prior screening on a battery of reading achievement tests. Two I I groups received training with one of the computer programs; the third group acted as a control and received the remedial reading program offered within the regular classroom. The groups met daily with a trained tutor for approximately 35 minutes, and were required to accumulate twenty hours of instruction. At the conclusion of the program, the pretest battery was repeated. No significant differences were found in the treatment effects of the two computer groups. Each of the two treatment groups was able to effect significantly improved reading word recognition and rate, relative to the control group. Comprehension gains were modest. The treatment groups demonstrated a significant gain, relative to the control group, on one of the three comprehension measures; only trends toward a gain were noted on the remaining two measures. The tutoring partnership appeared to be a viable alternative for the teacher seeking to provide individualized computerized remedial programs for adolescent unskilled readers. Both programs took advantage of computer technology in providing individualized drill and practice, instant feedback, and ongoing recordkeeping. With limited cautions, each of these programs was considered effective and practical for use with adolescent unskilled readers.

Geological image processing of petrographic thin sections using the rotating polarizer stage

One of the fundamental problems with image processing of petrographic thin sections is that the appearance (colour I intensity) of a mineral grain will vary with the orientation of the crystal lattice to the preferred direction of the polarizing filters on a petrographic microscope. This makes it very difficult to determine grain boundaries, grain orientation and mineral species from a single captured image. To overcome this problem, the Rotating Polarizer Stage was used to replace the fixed polarizer and analyzer on a standard petrographic microscope. The Rotating Polarizer Stage rotates the polarizers while the thin section remains stationary, allowing for better data gathering possibilities. Instead of capturing a single image of a thin section, six composite data sets are created by rotating the polarizers through 900 (or 1800 if quartz c-axes measurements need to be taken) in both plane and cross polarized light. The composite data sets can be viewed as separate images and consist of the average intensity image, the maximum intensity image, the minimum intensity image, the maximum position image, the minimum position image and the gradient image. The overall strategy used by the image processing system is to gather the composite data sets, determine the grain boundaries using the gradient image, classify the different mineral species present using the minimum and maximum intensity images and then perform measurements of grain shape and, where possible, partial crystallographic orientation using the maximum intensity and maximum position images.

The effects of computer assisted interactive fiction on the development of reading comprehension in grade five students

This study was undertaken in order to determine the effects of playing computer based text adventure games on the reading comprehension gains of students. Forty-five grade five students from one elementary school were randomly assigned to experimental and control groups, and were tested with regard to ability, achievement and reading skills. An experimental treatment, consisting of playing computer based interactive fiction games of the student's choice for fifteen minutes each day over an eight-week period, was administered. A comparison treatment engaged the control group in sustained silent reading of materials of the student's choice for an equal period of time. Following the experimental period all students were post-tested with an alternate form of the pre-test in reading skills, and gain scores were analysed. It was found that there were no significant differences in the gain scores of the experimental and control groups for overall reading comprehenSion, but the experimental group showed greater gains than the control group in the structural analysis reading sub-skill. Extreme variance in the data made generalization very difficult, but the findings indicated a potential for computer based interactive fiction as a useful tool for developing reading sl

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

Investigations On The Development Of An Ann Model & Visual Manipulation Approach For 2-D Dft Computation In Image Processing

This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

Video Object Tracking And Analysis For Computer Assisted Surgery

Pedicle screw insertion technique has made revolution in the surgical treatment of spinal fractures and spinal disorders. Although X- ray fluoroscopy based navigation is popular, there is risk of prolonged exposure to X- ray radiation. Systems that have lower radiation risk are generally quite expensive. The position and orientation of the drill is clinically very important in pedicle screw fixation. In this paper, the position and orientation of the marker on the drill is determined using pattern recognition based methods, using geometric features, obtained from the input video sequence taken from CCD camera. A search is then performed on the video frames after preprocessing, to obtain the exact position and orientation of the drill. An animated graphics, showing the instantaneous position and orientation of the drill is then overlaid on the processed video for real time drill control and navigation