197 research outputs found

    Retinal Image Registration and Comparison for Clinical Decision Support

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    Background For eye diseases, such as glaucoma and age-related macular degeneration (ARMD), involved in long-term degeneration procedure, longitudinal comparison of retinal images is a common step for reliable diagnosis of these kinds of diseases. Aims To provide a retinal image registration approach for longitudinal retinal image alignment and comparison. Method Two image registration solutions were proposed for facing different image qualities of retinal images to make the registration methods more robust and feasible in a clinical application system. Results Thirty pairs of longitudinal retinal images were used for the registration test. The experiments showed both solutions provided good performance for the accurate image registrations with efficiency. Conclusion We proposed a set of retinal image registration solutions for longitudinal retinal image observation and comparison targeting a clinical application environment

    Superimposition of eye fundus images for longitudinal analysis from large public health databases

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    In this paper, a method is presented for superimposition (i.e. registration) of eye fundus images from persons with diabetes screened over many years for diabetic retinopathy. The method is fully automatic and robust to camera changes and colour variations across the images both in space and time. All the stages of the process are designed for longitudinal analysis of cohort public health databases where retinal examinations are made at approximately yearly intervals. The method relies on a model correcting two radial distortions and an affine transformation between pairs of images which is robustly fitted on salient points. Each stage involves linear estimators followed by non-linear optimisation. The model of image warping is also invertible for fast computation. The method has been validated (1) on a simulated montage and (2) on public health databases with 69 patients with high quality images (271 pairs acquired mostly with different types of camera and 268 pairs acquired mostly with the same type of camera) with success rates of 92% and 98%, and five patients (20 pairs) with low quality images with a success rate of 100%. Compared to two state-of-the-art methods, ours gives better results.Comment: This is an author-created, un-copyedited version of an article published in Biomedical Physics \& Engineering Express. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://doi.org/10.1088/2057-1976/aa7d1

    Incorporating spatial and temporal information for microaneurysm detection in retinal images

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    The retina of the human eye has the potential to reveal crucial information about several diseases such as diabetes. Several signs such as microaneurysms (MA) manifest themselves as early indicators of Diabetic Retinopathy (DR). Detection of these early signs is important from a clinical perspective in order to suggest appropriate treatment for DR patients. This work aims to improve the detection accuracy of MAs in colour fundus images. While it is expected that multiple images per eye are available in a clinical setup, proposed segmentation algorithms in the literature do not make use of these multiple images. This work introduces a novel MA detection algorithm and a framework for combining spatial and temporal images. A new MA detection method has been proposed which uses a Gaussian matched filter and an ensemble classifier with 70 features for the detection of candidates. The proposed method was evaluated on three public datasets (171 images in total) and has shown improvement in performance for two of the sets when compared to a state-of-the-art method. For lesion-based performance, the proposed method has achieved Retinopathy Online Challenge (ROC) scores of 0.3923, 2109 and 0.1523 in the MESSIDOR, DIARETDB1 and ROC datasets respectively. Based on the ensemble algorithm, a framework for the information combination is developed and consists of image alignment, detecting candidates with likelihood scores, matching candidates from aligned images, and finally fusing the scores from the aligned image pairs. This framework is used to combine information both spatially and temporally. A dataset of 320 images that consists of both spatial and temporal pairs was used for the evaluation. An improvement of performance by 2% is shown after combining spatial information. The framework is applied to temporal image pairs and the results of combining temporal information are analyzed and discussed

    The development of a hybrid virtual reality/video view-morphing display system for teleoperation and teleconferencing

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    Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2000.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 84-89).The goal of this study is to extend the desktop panoramic static image viewer concept (e.g., Apple QuickTime VR; IPIX) to support immersive real time viewing, so that an observer wearing a head-mounted display can make free head movements while viewing dynamic scenes rendered in real time stereo using video data obtained from a set of fixed cameras. Computational experiments by Seitz and others have demonstrated the feasibility of morphing image pairs to render stereo scenes from novel, virtual viewpoints. The user can interact both with morphed real world video images, and supplementary artificial virtual objects (“Augmented Reality”). The inherent congruence of the real and artificial coordinate frames of this system reduces registration errors commonly found in Augmented Reality applications. In addition, the user’s eyepoint is computed locally so that any scene lag resulting from head movement will be less than those from alternative technologies using remotely controlled ground cameras. For space applications, this can significantly reduce the apparent lag due to satellite communication delay. This hybrid VR/view-morphing display (“Virtual Video”) has many important NASA applications including remote teleoperation, crew onboard training, private family and medical teleconferencing, and telemedicine. The technical objective of this study developed a proof-of-concept system using a 3D graphics PC workstation of one of the component technologies, Immersive Omnidirectional Video, of Virtual Video. The management goal identified a system process for planning, managing, and tracking the integration, test and validation of this phased, 3-year multi-university research and development program.by William E. Hutchison.S.M

    Vision Sensors and Edge Detection

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    Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing

    Comprehensive retinal image analysis: image processing and feature extraction techniques oriented to the clinical task

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    Medical digital imaging has become a key element of modern health care procedures. It provides a visual documentation, a permanent record for the patients, and most importantly the ability to extract information about many diseases. Ophthalmology is a field that is heavily dependent on the analysis of digital images because they can aid in establishing an early diagnosis even before the first symptoms appear. This dissertation contributes to the digital analysis of such images and the problems that arise along the imaging pipeline, a field that is commonly referred to as retinal image analysis. We have dealt with and proposed solutions to problems that arise in retinal image acquisition and longitudinal monitoring of retinal disease evolution. Specifically, non-uniform illumination, poor image quality, automated focusing, and multichannel analysis. However, there are many unavoidable situations in which images of poor quality, like blurred retinal images because of aberrations in the eye, are acquired. To address this problem we have proposed two approaches for blind deconvolution of blurred retinal images. In the first approach, we consider the blur to be space-invariant and later in the second approach we extend the work and propose a more general space-variant scheme. For the development of the algorithms we have built preprocessing solutions that have enabled the extraction of retinal features of medical relevancy, like the segmentation of the optic disc and the detection and visualization of longitudinal structural changes in the retina. Encouraging experimental results carried out on real retinal images coming from the clinical setting demonstrate the applicability of our proposed solutions

    Correction of Errors in Time of Flight Cameras

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    En esta tesis se aborda la corrección de errores en cámaras de profundidad basadas en tiempo de vuelo (Time of Flight - ToF). De entre las más recientes tecnologías, las cámaras ToF de modulación continua (Continuous Wave Modulation - CWM) son una alternativa prometedora para la creación de sensores compactos y rápidos. Sin embargo, existen gran variedad de errores que afectan notablemente la medida de profundidad, poniendo en compromiso posibles aplicaciones. La corrección de dichos errores propone un reto desafiante. Actualmente, se consideran dos fuentes principales de error: i) sistemático y ii) no sistemático. Mientras que el primero admite calibración, el último depende de la geometría y el movimiento relativo de la escena. Esta tesis propone métodos que abordan i) la distorsión sistemática de profundidad y dos de las fuentes de error no sistemático más relevantes: ii.a) la interferencia por multicamino (Multipath Interference - MpI) y ii.b) los artefactos de movimiento. La distorsión sistemática de profundidad en cámaras ToF surge principalmente debido al uso de señales sinusoidales no perfectas para modular. Como resultado, las medidas de profundidad aparecen distorsionadas, pudiendo ser reducidas con una etapa de calibración. Esta tesis propone un método de calibración basado en mostrar a la cámara un plano en diferentes posiciones y orientaciones. Este método no requiere de patrones de calibración y, por tanto, puede emplear los planos, que de manera natural, aparecen en la escena. El método propuesto encuentra una función que obtiene la corrección de profundidad correspondiente a cada píxel. Esta tesis mejora los métodos existentes en cuanto a precisión, eficiencia e idoneidad. La interferencia por multicamino surge debido a la superposición de la señal reflejada por diferentes caminos con la reflexión directa, produciendo distorsiones que se hacen más notables en superficies convexas. La MpI es la causa de importantes errores en la estimación de profundidad en cámaras CWM ToF. Esta tesis propone un método que elimina la MpI a partir de un solo mapa de profundidad. El enfoque propuesto no requiere más información acerca de la escena que las medidas ToF. El método se fundamenta en un modelo radio-métrico de las medidas que se emplea para estimar de manera muy precisa el mapa de profundidad sin distorsión. Una de las tecnologías líderes para la obtención de profundidad en imagen ToF está basada en Photonic Mixer Device (PMD), la cual obtiene la profundidad mediante el muestreado secuencial de la correlación entre la señal de modulación y la señal proveniente de la escena en diferentes desplazamientos de fase. Con movimiento, los píxeles PMD capturan profundidades diferentes en cada etapa de muestreo, produciendo artefactos de movimiento. El método propuesto en esta tesis para la corrección de dichos artefactos destaca por su velocidad y sencillez, pudiendo ser incluido fácilmente en el hardware de la cámara. La profundidad de cada píxel se recupera gracias a la consistencia entre las muestras de correlación en el píxel PMD y de la vecindad local. Este método obtiene correcciones precisas, reduciendo los artefactos de movimiento enormemente. Además, como resultado de este método, puede obtenerse el flujo óptico en los contornos en movimiento a partir de una sola captura. A pesar de ser una alternativa muy prometedora para la obtención de profundidad, las cámaras ToF todavía tienen que resolver problemas desafiantes en relación a la corrección de errores sistemáticos y no sistemáticos. Esta tesis propone métodos eficaces para enfrentarse con estos errores

    Three-dimensional modeling of the human jaw/teeth using optics and statistics.

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    Object modeling is a fundamental problem in engineering, involving talents from computer-aided design, computational geometry, computer vision and advanced manufacturing. The process of object modeling takes three stages: sensing, representation, and analysis. Various sensors may be used to capture information about objects; optical cameras and laser scanners are common with rigid objects, while X-ray, CT and MRI are common with biological organs. These sensors may provide a direct or an indirect inference about the object, requiring a geometric representation in the computer that is suitable for subsequent usage. Geometric representations that are compact, i.e., capture the main features of the objects with a minimal number of data points or vertices, fall into the domain of computational geometry. Once a compact object representation is in the computer, various analysis steps can be conducted, including recognition, coding, transmission, etc. The subject matter of this dissertation is object reconstruction from a sequence of optical images using shape from shading (SFS) and SFS with shape priors. The application domain is dentistry. Most of the SFS approaches focus on the computational part of the SFS problem, i.e. the numerical solution. As a result, the imaging model in most conventional SFS algorithms has been simplified under three simple, but restrictive assumptions: (1) the camera performs an orthographic projection of the scene, (2) the surface has a Lambertian reflectance and (3) the light source is a single point source at infinity. Unfortunately, such assumptions are no longer held in the case of reconstruction of real objects as intra-oral imaging environment for human teeth. In this work, we introduce a more realistic formulation of the SFS problem by considering the image formation components: the camera, the light source, and the surface reflectance. This dissertation proposes a non-Lambertian SFS algorithm under perspective projection which benefits from camera calibration parameters. The attenuation of illumination is taken account due to near-field imaging. The surface reflectance is modeled using the Oren-Nayar-Wolff model which accounts for the retro-reflection case. In this context, a new variational formulation is proposed that relates an evolving surface model with image information, taking into consideration that the image is taken by a perspective camera with known parameters. A new energy functional is formulated to incorporate brightness, smoothness and integrability constraints. In addition, to further improve the accuracy and practicality of the results, 3D shape priors are incorporated in the proposed SFS formulation. This strategy is motivated by the fact that humans rely on strong prior information about the 3D world around us in order to perceive 3D shape information. Such information is statistically extracted from training 3D models of the human teeth. The proposed SFS algorithms have been used in two different frameworks in this dissertation: a) holistic, which stitches a sequence of images in order to cover the entire jaw, and then apply the SFS, and b) piece-wise, which focuses on a specific tooth or a segment of the human jaw, and applies SFS using physical teeth illumination characteristics. To augment the visible portion, and in order to have the entire jaw reconstructed without the use of CT or MRI or even X-rays, prior information were added which gathered from a database of human jaws. This database has been constructed from an adult population with variations in teeth size, degradation and alignments. The database contains both shape and albedo information for the population. Using this database, a novel statistical shape from shading (SSFS) approach has been created. Extending the work on human teeth analysis, Finite Element Analysis (FEA) is adapted for analyzing and calculating stresses and strains of dental structures. Previous Finite Element (FE) studies used approximate 2D models. In this dissertation, an accurate three-dimensional CAD model is proposed. 3D stress and displacements of different teeth type are successfully carried out. A newly developed open-source finite element solver, Finite Elements for Biomechanics (FEBio), has been used. The limitations of the experimental and analytical approaches used for stress and displacement analysis are overcome by using FEA tool benefits such as dealing with complex geometry and complex loading conditions
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