Effect of age on upper and lower eyelid saccades

To study the effect of age on the metrics of upper and lower eyelid saccades, eyelid movement of two groups of 30 subjects each were measured using computed image analysis. The patients were divided on the basis of age into a younger group (20-30 years) and an older group (60-91 years). Eyelid saccade functions were fitted by the damped harmonic oscillator model. Amplitude and peak velocity were used to compare the effect of age on the saccades of the upper and lower eyelid. There was no statistically significant difference in saccade amplitude between groups for the upper eyelid (mean ± SEM; upward, young = 9.18 ± 0.32 mm, older = 8.93 ± 0.31 mm, t = 0.56, P = 0.58; downward, young = 9.11 ± 0.27 mm, older = 8.86 ± 0.32 mm, t = 0.58, P = 0.56) However, there was a clear decline in the peak velocity of the upper eyelid saccades of older subjects (upward, young = 59.06 ± 2.34 mm/s, older = 50.12 ± 1.95 mm/s, t = 2.93, P = 0.005; downward, young = 71.78 ± 1.78 mm/s, older = 60.29 ± 2.62 mm/s, t = 3.63, P = 0.0006). In contrast, for the lower eyelid there was a clear increase of saccade amplitude in the elderly group (upward, young = 2.27 ± 0.09 mm, older = 2.98 ± 0.15 mm, t = 4.33, P < 0.0001; downward, young = 2.21 ± 0.10 mm, older = 2.96 ± 0.17 mm, t = 3.85, P < 0.001). These data suggest that the aging process affects the metrics of the lid saccades in a different manner according to the eyelid. In the upper eyelid the lower tension exerted by a weak aponeurosis is reflected only on the peak velocity of the saccades. In the lower eyelid, age is accompanied by an increase in saccade amplitude which indicates that the force transmission to the lid is not affected in the elderly.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

A clinical gamma camera-based pinhole collimated system for high resolution small animal SPECT imaging

The main objective of the present study was to upgrade a clinical gamma camera to obtain high resolution tomographic images of small animal organs. The system is based on a clinical gamma camera to which we have adapted a special-purpose pinhole collimator and a device for positioning and rotating the target based on a computer-controlled step motor. We developed a software tool to reconstruct the target’s three-dimensional distribution of emission from a set of planar projections, based on the maximum likelihood algorithm. We present details on the hardware and software implementation. We imaged phantoms and heart and kidneys of rats. When using pinhole collimators, the spatial resolution and sensitivity of the imaging system depend on parameters such as the detector-to-collimator and detector-to-target distances and pinhole diameter. In this study, we reached an object voxel size of 0.6 mm and spatial resolution better than 2.4 and 1.7 mm full width at half maximum when 1.5- and 1.0-mm diameter pinholes were used, respectively. Appropriate sensitivity to study the target of interest was attained in both cases. Additionally, we show that as few as 12 projections are sufficient to attain good quality reconstructions, a result that implies a significant reduction of acquisition time and opens the possibility for radiotracer dynamic studies. In conclusion, a high resolution single photon emission computed tomography (SPECT) system was developed using a commercial clinical gamma camera, allowing the acquisition of detailed volumetric images of small animal organs. This type of system has important implications for research areas such as Cardiology, Neurology or Oncology.

Shelf life of minimally processed carrot and green pepper

The postharvest losses of horticultural products justify the use of preservation techniques. The processing not only adds value to the products, but also makes the products more convenient to the consumers. The objective of this research was to define the methodologies for the minimal processing of carrot and green pepper as to the type and intensity of the adoption of conservation techniques, and to monitor the products after processing through microbiological, physicochemical and nutritional analysis. The vegetables were washed and they were immersed in cold (7ºC) water with 100 mg L-1 free chlorine for sanitation, followed by centrifugation for 5 min. The product was put into BOPP/LDPE (biaxially orientated polypropylene/low-density polyethylene) plastic bags, which were sealed under atmospheric air, vacuum and modified atmosphere (2% O2, 10% CO2, 88% N2) and stored at 1ºC±1ºC. The approximate composition of the vegetables stayed stable during the storage period, in the three tested treatments. The contents of vitamin C for the samples of minimally processed carrot and green pepper did not present differences among treatments. The contents of beta-carotene decreased slightly during the storage period for the minimally processed carrot and green pepper. After processing, carrot and green pepper had psychrotrophic counts of 10²-10(5) and 10³-10(6) CFU g-1, respectively. Anaerobic mesophiles and total coliforms were found in green peppers, representing 1.6x10³ - 7.4x10(5) and <10.g-1 - 7.4x10(5), respectively. Total and fecal coliforms, anaerobic mesophiles and Salmonella were not found in carrots. Salmonella was not found in green pepper.

Quality assurance of refuse derived fuel with machine vision

This thesis studies the use of machine vision in RDF quality assurance and manufacturing. Currently machine vision is used in recycling and material detection and some commer- cial products are available in the market. In this thesis an on-line machine vision system is proposed for characterizing particle size. The proposed machine vision system is based on the mapping between image segmenta- tion and the ground truth of the particle size. The results shows that the implementation of such machine vision system is feasible.

Real-time monitoring of laser scribing process utilizing high-speed camera

Currently, laser scribing is growing material processing method in the industry. Benefits of laser scribing technology are studied for example for improving an efficiency of solar cells. Due high-quality requirement of the fast scribing process, it is important to monitor the process in real time for detecting possible defects during the process. However, there is a lack of studies of laser scribing real time monitoring. Commonly used monitoring methods developed for other laser processes such a laser welding, are sufficient slow and existed applications cannot be implemented in fast laser scribing monitoring. The aim of this thesis is to find a method for laser scribing monitoring with a high-speed camera and evaluate reliability and performance of the developed monitoring system with experiments. The laser used in experiments is an IPG ytterbium pulsed fiber laser with 20 W maximum average power and Scan head optics used in the laser is Scanlab’s Hurryscan 14 II with an f100 tele-centric lens. The camera was connected to laser scanner using camera adapter to follow the laser process. A powerful fully programmable industrial computer was chosen for executing image processing and analysis. Algorithms for defect analysis, which are based on particle analysis, were developed using LabVIEW system design software. The performance of the algorithms was analyzed by analyzing a non-moving image from the scribing line with resolution 960x20 pixel. As a result, the maximum analysis speed was 560 frames per second. Reliability of the algorithm was evaluated by imaging scribing path with a variable number of defects 2000 mm/s when the laser was turned off and image analysis speed was 430 frames per second. The experiment was successful and as a result, the algorithms detected all defects from the scribing path. The final monitoring experiment was performed during a laser process. However, it was challenging to get active laser illumination work with the laser scanner due physical dimensions of the laser lens and the scanner. For reliable error detection, the illumination system is needed to be replaced.

Control of Bubbling Fluidized Bed Conditions

The objectives of this master’s thesis were to understand the importance of bubbling fluidized bed (BFB) conditions and to find out how digital image processing and acoustic emission technology can help in monitoring the bed quality. An acoustic emission (AE) measurement system and a bottom ash camera system were evaluated in acquiring information about the bed conditions. The theory part of the study describes the fundamentals of BFB boiler and evaluates the characteristics of bubbling bed. Causes and effects of bed material coarsening are explained. The ways and methods to monitor the behaviour of BFB are determined. The study introduces the operating principles of AE technology and digital image processing. The empirical part of the study describes an experimental arrangement and results of a case study at an industrial BFB boiler. Sand consumption of the boiler was reduced by optimization of bottom ash handling and sand feeding. Furthermore, data from the AE measurement system and the bottom ash camera system was collected. The feasibility of these two systems was evaluated. The particle size of bottom ash and the changes in particle size distribution were monitored during the test period. Neither of the systems evaluated was ready to serve in bed quality control accurately or fast enough. Particle size distributions according to the bottom ash camera did not correspond to the results of manual sieving. Comprehensive interpretation of the collected AE data requires much experience. Both technologies do have potential and with more research and development they may enable acquiring reliable and real-time information about the bed conditions. This information could help to maintain disturbance-free combustion process and to optimize bottom ash handling system.

Quadtree representation and compression of spatial data

Spatial data representation and compression has become a focus issue in computer graphics and image processing applications. Quadtrees, as one of hierarchical data structures, basing on the principle of recursive decomposition of space, always offer a compact and efficient representation of an image. For a given image, the choice of quadtree root node plays an important role in its quadtree representation and final data compression. The goal of this thesis is to present a heuristic algorithm for finding a root node of a region quadtree, which is able to reduce the number of leaf nodes when compared with the standard quadtree decomposition. The empirical results indicate that, this proposed algorithm has quadtree representation and data compression improvement when in comparison with the traditional method.

Segmentation d’images intravasculaires ultrasonores

L'imagerie intravasculaire ultrasonore (IVUS) est une technologie médicale par cathéter qui produit des images de coupe des vaisseaux sanguins. Elle permet de quantifier et d'étudier la morphologie de plaques d'athérosclérose en plus de visualiser la structure des vaisseaux sanguins (lumière, intima, plaque, média et adventice) en trois dimensions. Depuis quelques années, cette méthode d'imagerie est devenue un outil de choix en recherche aussi bien qu'en clinique pour l'étude de la maladie athérosclérotique. L'imagerie IVUS est par contre affectée par des artéfacts associés aux caractéristiques des capteurs ultrasonores, par la présence de cônes d'ombre causés par les calcifications ou des artères collatérales, par des plaques dont le rendu est hétérogène ou par le chatoiement ultrasonore (speckle) sanguin. L'analyse automatisée de séquences IVUS de grande taille représente donc un défi important. Une méthode de segmentation en trois dimensions (3D) basée sur l'algorithme du fast-marching à interfaces multiples est présentée. La segmentation utilise des attributs des régions et contours des images IVUS. En effet, une nouvelle fonction de vitesse de propagation des interfaces combinant les fonctions de densité de probabilité des tons de gris des composants de la paroi vasculaire et le gradient des intensités est proposée. La segmentation est grandement automatisée puisque la lumière du vaisseau est détectée de façon entièrement automatique. Dans une procédure d'initialisation originale, un minimum d'interactions est nécessaire lorsque les contours initiaux de la paroi externe du vaisseau calculés automatiquement sont proposés à l'utilisateur pour acceptation ou correction sur un nombre limité d'images de coupe longitudinale. La segmentation a été validée à l'aide de séquences IVUS in vivo provenant d'artères fémorales provenant de différents sous-groupes d'acquisitions, c'est-à-dire pré-angioplastie par ballon, post-intervention et à un examen de contrôle 1 an suivant l'intervention. Les résultats ont été comparés avec des contours étalons tracés manuellement par différents experts en analyse d'images IVUS. Les contours de la lumière et de la paroi externe du vaisseau détectés selon la méthode du fast-marching sont en accord avec les tracés manuels des experts puisque les mesures d'aire sont similaires et les différences point-à-point entre les contours sont faibles. De plus, la segmentation par fast-marching 3D s'est effectuée en un temps grandement réduit comparativement à l'analyse manuelle. Il s'agit de la première étude rapportée dans la littérature qui évalue la performance de la segmentation sur différents types d'acquisition IVUS. En conclusion, la segmentation par fast-marching combinant les informations des distributions de tons de gris et du gradient des intensités des images est précise et efficace pour l'analyse de séquences IVUS de grandes tailles. Un outil de segmentation robuste pourrait devenir largement répandu pour la tâche ardue et fastidieuse qu'est l'analyse de ce type d'images.

Les cartes fonctionnelles dans le cortex visuel du chat : nouvelles stratégies d’évaluation en imagerie optique et mise en évidence de l’organisation anatomo-fonctionnelle

Le regroupement des neurones de propriétés similaires est à l’origine de modules permettant d’optimiser l’analyse de l’information. La conséquence est la présence de cartes fonctionnelles dans le cortex visuel primaire de certains mammifères pour de nombreux paramètres tels que l’orientation, la direction du mouvement ou la position des stimuli (visuotopie). Le premier volet de cette thèse est consacré à caractériser l’organisation modulaire dans le cortex visuel primaire pour un paramètre fondamental, la suppression centre / pourtour et au delà du cortex visuel primaire (dans l’aire 21a), pour l’orientation et la direction. Toutes les études ont été effectuées à l’aide de l’imagerie optique des signaux intrinsèques sur le cortex visuel du chat anesthésié. La quantification de la modulation par la taille des stimuli à permis de révéler la présence de modules de forte et de faible suppression par le pourtour dans le cortex visuel primaire (aires 17 et 18). Ce type d’organisation n’avait été observé jusqu’ici que dans une aire de plus haut niveau hiérarchique chez le primate. Une organisation modulaire pour l’orientation, similaire à celle observée dans le cortex visuel primaire a été révélée dans l’aire 21a. Par contre, contrairement à l’aire 18, l’aire 21a ne semblait pas être organisée en domaine de direction. L’ensemble de ces résultats pourront permettre d’alimenter les connaissances sur l’organisation anatomo-fonctionnelle du cortex visuel du chat mais également de mieux comprendre les facteurs qui déterminent la présence d’une organisation modulaire. Le deuxième volet abordé dans cette thèse s’est intéressé à l’amélioration de l’aspect quantitatif apporté par l’analyse temporelle en imagerie optique des signaux intrinsèques. Cette nouvelle approche, basée sur l’analyse de Fourier a permis d’augmenter considérablement le rapport signal / bruit des enregistrements. Toutefois, cette analyse ne s’est basée jusqu’ici que sur la quantification d’une seule harmonique ce qui a limité son emploi à la cartographie de l’orientation et de rétinotopie uniquement. En exploitant les plus hautes harmoniques, un modèle a été proposé afin d’estimer la taille des champs récepteurs et la sélectivité à la direction. Ce modèle a par la suite été validé par des approches conventionnelles dans le cortex visuel primaire.

Évaluation d'un modèle a priori basé sur un seuillage de la TCD en super-résolution et comparaison avec d'autres modèles a priori

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Video-based postural sway analysis in a controlled environment

À mesure que la population des personnes agées dans les pays industrialisés augmente au fil de années, les ressources nécessaires au maintien du niveau de vie de ces personnes augmentent aussi. Des statistiques montrent que les chutes sont l’une des principales causes d’hospitalisation chez les personnes agées, et, de plus, il a été démontré que le risque de chute d’une personne agée a une correlation avec sa capacité de maintien de l’équilibre en étant debout. Il est donc d’intérêt de développer un système automatisé pour analyser l’équilibre chez une personne, comme moyen d’évaluation objective. Dans cette étude, nous avons proposé l’implémentation d’un tel système. En se basant sur une installation simple contenant une seule caméra sur un trépied, on a développé un algorithme utilisant une implémentation de la méthode de détection d’objet de Viola-Jones, ainsi qu’un appariement de gabarit, pour suivre autant le mouvement latéral que celui antérieur-postérieur d’un sujet. On a obtenu des bons résultats avec les deux types de suivi, cependant l’algorithme est sensible aux conditions d’éclairage, ainsi qu’à toute source de bruit présent dans les images. Il y aurait de l’intérêt, comme développement futur, d’intégrer les deux types de suivi, pour ainsi obtenir un seul ensemble de données facile à interpréter.

A robust algorithm for segmenting fluorescence images and its application to single-molecule counting

La microscopie par fluorescence de cellules vivantes produit de grandes quantités de données. Ces données sont composées d’une grande diversité au niveau de la forme des objets d’intérêts et possèdent un ratio signaux/bruit très bas. Pour concevoir un pipeline d’algorithmes efficaces en traitement d’image de microscopie par fluorescence, il est important d’avoir une segmentation robuste et fiable étant donné que celle-ci constitue l’étape initiale du traitement d’image. Dans ce mémoire, je présente MinSeg, un algorithme de segmentation d’image de microscopie par fluorescence qui fait peu d’assomptions sur l’image et utilise des propriétés statistiques pour distinguer le signal par rapport au bruit. MinSeg ne fait pas d’assomption sur la taille ou la forme des objets contenus dans l’image. Par ce fait, il est donc applicable sur une grande variété d’images. Je présente aussi une suite d’algorithmes pour la quantification de petits complexes dans des expériences de microscopie par fluorescence de molécules simples utilisant l’algorithme de segmentation MinSeg. Cette suite d’algorithmes a été utilisée pour la quantification d’une protéine nommée CENP-A qui est une variante de l’histone H3. Par cette technique, nous avons trouvé que CENP-A est principalement présente sous forme de dimère.

Scoliosis Follow-Up Using Noninvasive Trunk Surface Acquisition

Adolescent idiopathic scoliosis (AIS) is a musculoskeletal pathology. It is a complex spinal curvature in a 3-D space that also affects the appearance of the trunk. The clinical follow-up of AIS is decisive for its management. Currently, the Cobb angle, which is measured from full spine radiography, is the most common indicator of the scoliosis progression. However, cumulative exposure to X-rays radiation increases the risk for certain cancers. Thus, a noninvasive method for the identification of the scoliosis progression from trunk shape analysis would be helpful. In this study, a statistical model is built from a set of healthy subjects using independent component analysis and genetic algorithm. Based on this model, a representation of each scoliotic trunk from a set of AIS patients is computed and the difference between two successive acquisitions is used to determine if the scoliosis has progressed or not. This study was conducted on 58 subjects comprising 28 healthy subjects and 30 AIS patients who had trunk surface acquisitions in upright standing posture. The model detects 93% of the progressive cases and 80% of the nonprogressive cases. Thus, the rate of false negatives, representing the proportion of undetected progressions, is very low, only 7%. This study shows that it is possible to perform a scoliotic patient's follow-up using 3-D trunk image analysis, which is based on a noninvasive acquisition technique.