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Author |
Jaime Lopez-Krahe; Josep Llados; Enric Marti |
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Title |
Architectural Floor Plan Analysis |
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2000 |
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CVonline |
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Edimburg, UK |
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University of Edinburgh |
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Robert B. Fisher |
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online pdf |
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DAG;IAM |
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IAM @ iam @ LLM2000 |
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1561 |
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Author |
Eric Amiel |
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Title |
Visualisation de vaisseaux sanguins |
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2005 |
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Rapport de Stage |
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Université Paul Sabatier Toulouse III |
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Bachelor's thesis |
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Université Paul Sabatier Toulouse III |
Place of Publication |
Toulouse |
Editor |
Enric Marti |
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Language |
French |
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French |
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IUP Systèmes Intelligents |
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IAM |
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IAM @ iam @ Ami2005 |
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1690 |
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Author |
Joan M. Nuñez |
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Title |
Computer vision techniques for characterization of finger joints in X-ray image |
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Report |
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Year |
2011 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
165 |
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Rheumatoid arthritis, X-ray, Sharp Van der Heijde, joint characterization, sclerosis detection, bone detection, edge, ridge |
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Abstract |
Rheumatoid arthritis (RA) is an autoimmune inflammatory type of arthritis which mainly affects hands on its first stages. Though it is a chronic disease and there is no cure for it, treatments require an accurate assessment of illness evolution. Such assessment is based on evaluation of hand X-ray images by using one of the several available semi-quantitative methods. This task requires highly trained medical personnel. That is why the automation of the assessment would allow professionals to save time and effort. Two stages are involved in this task. Firstly, the joint detection, afterwards, the joint characterization. Unlike the little existing previous work, this contribution clearly separates those two stages and sets the foundations of a modular assessment system focusing on the characterization stage. A hand joint dataset is created and an accurate data analysis is achieved in order to identify relevant features. Since the sclerosis and the lower bone were decided to be the most important features, different computer vision techniques were used in order to develop a detector system for both of them. Joint space width measures are provided and their correlation with Sharp-Van der Heijde is verified |
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Address |
Bellaterra (Barcelona) |
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Corporate Author |
Computer Vision Center |
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Master's thesis |
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Dr. Fernando Vilariño and Dra. Debora Gil |
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MV;IAM; |
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IAM @ iam @ Nuñ2011 |
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1795 |
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Author |
Carles Sanchez |
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Title |
Tracheal ring detection in bronchoscopy |
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Report |
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2011 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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168 |
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Bronchoscopy, tracheal ring, segmentation |
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Abstract |
Endoscopy is the process in which a camera is introduced inside a human.
Given that endoscopy provides realistic images (in contrast to other modalities) and allows non-invase minimal intervention procedures (which can aid in diagnosis and surgical interventions), its use has spreaded during last decades.
In this project we will focus on bronchoscopic procedures, during which the camera is introduced through the trachea in order to have a diagnostic of the patient. The diagnostic interventions are focused on: degree of stenosis (reduction in tracheal area), prosthesis or early diagnosis of tumors. In the first case, assessment of the luminal area and the calculation of the diameters of the tracheal rings are required. A main limitation is that all the process is done by hand,
which means that the doctor takes all the measurements and decisions just by looking at the screen. As far as we know there is no computational framework for helping the doctors in the diagnosis.
This project will consist of analysing bronchoscopic videos in order to extract useful information for the diagnostic of the degree of stenosis. In particular we will focus on segmentation of the tracheal rings. As a result of this project several strategies (for detecting tracheal rings) had been implemented in order to compare their performance. |
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Master's thesis |
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Debora Gil, F.Javier Sanchez |
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english |
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english |
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IAM;MV |
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IAM @ iam @ San2011 |
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1841 |
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Author |
Jaume Garcia |
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Title |
Propagacio de fronts per a la segmentacio en imatges IVUS |
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Report |
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2002 |
Publication |
Technical Report |
Abbreviated Journal |
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65 |
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CVC (UAB) |
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IAM |
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Call Number |
IAM @ iam @ Gar2002 |
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328 |
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Author |
Albert Andaluz |
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Title |
LV Contour Segmentation in TMR images using Semantic Description of Tissue and Prior Knowledge Correction |
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Report |
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2009 |
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CVC Technical Report |
Abbreviated Journal |
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Volume |
142 |
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Keywords |
Active Contour Models; Snakes; Active Shape Models; Deformable Templates; Left Ventricle Segmentation; Generalized Orthogonal Procrustes Analysis; Harmonic Phase Flow; Principal Component Analysis; Tagged Magnetic Resonance |
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Abstract |
The Diagnosis of Left Ventricle (LV) pathologies is related to regional wall motion analysis. Health indicator scores such as the rotation and the torsion are useful for the diagnose of the Left Ventricle (LV) function. However, this requires proper identification of LV segments. On one hand, manual segmentation is robust, but it is slow and requires medical expertise. On the other hand, the tag pattern in Tagged Magnetic Resonance (TMR) sequences is a problem for the automatic segmentation of the LV boundaries. Consequently, we propose a method based in the classical formulation of parametric Snakes, combined with Active Shape models. Our semantic definition of the LV is tagged tissue that experiences motion in the systolic cycle. This defines two energy potentials for the Snake convergence. Additionally, the mean shape corrects excessive deviation from the anatomical shape. We have validated our approach in 15 healthy volunteers and two short axis cuts. In this way, we have compared the automatic segmentations to manual shapes outlined by medical experts. Also, we have explored the accuracy of clinical scores computed using automatic contours. The results show minor divergence in the approximation and the manual segmentations as well as robust computation of clinical scores in all cases. From this we conclude that the proposed method is a promising support tool for clinical analysis. |
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Master's thesis |
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Bellaterra 08193, Barcelona, Spain |
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IAM; |
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IAM @ iam @ And2009 |
Serial |
1667 |
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Author |
Jaume Garcia |
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Title |
Generalized Active Shape Models Applied to Cardiac Function Analysis |
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Report |
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Year |
2004 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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78 |
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Keywords |
Cardiac Analysis; Deformable Models; Active Contour Models; Active Shape Models; Tagged MRI; HARP; Contrast Echocardiography. |
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Abstract |
Medical imaging is very useful in the assessment and treatment of many diseases. To deal with the great amount of data provided by imaging scanners and extract quantitative information that physicians can interpret, many analysis algorithms have been developed. Any process of analysis always consists of a first step of segmenting some particular structure. In medical imaging, structures are not always well defined and suffer from noise artifacts thus, ordinary segmentation methods are not well suited. The ones that seem to give better results are those based on deformable models. Nevertheless, despite their capability of mixing image features together with smoothness constraints that may compensate for image irregularities, these are naturally local methods, i. e., each node of the active contour evolve taking into account information about its neighbors and some other weak constraints about flexibility and smoothness, but not about the global shape that they should find. Due to the fact that structures to be segmented are the same for all cases but with some inter and intra-patient variation, the incorporation of a priori knowledge about shape in the segmentation method will provide robustness to it. Active Shape Models is an algorithm based on the creation of a shape model called Point Distribution Model. It performs a segmentation using only shapes similar than those previously learned from a training set that capture most of the variation presented by the structure. This algorithm works by updating shape nodes along a normal segment which often can be too restrictive. For this reason we propose a generalization of this algorithm that we call Generalized Active Shape Models and fully integrates the a priori knowledge given by the Point Distribution Model with deformable models or any other appropriate segmentation method. Two different applications to cardiac imaging of this generalized method are developed and promising results are shown. |
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CVC (UAB) |
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Master's thesis |
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IAM; |
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IAM @ iam @ Gar2004 |
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1513 |
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Author |
Debora Gil |
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Title |
Regularized Curvature Flow |
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2002 |
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CVC Technical Report |
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63 |
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Computer Vision Centre |
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IAM; |
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IAM @ iam @ Gil2002 |
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1518 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Curvature based Distance Maps |
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2003 |
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CVC Technical Report |
Abbreviated Journal |
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70 |
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Computer Vision Center |
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IAM @ iam @ GIR2003a |
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1534 |
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Author |
Aura Hernandez-Sabate |
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Title |
Automatic adventitia segmentation in IntraVascular UltraSound images |
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2005 |
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CVC Technical Report |
Abbreviated Journal |
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85 |
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A usual tool in cardiac disease diagnosis is vessel plaque assessment by analysis of IVUS sequences. Manual detection of lumen-intima, intima-media and media-adventitia vessel borders is the main activity of physicians in the process of plaque quantification. Large variety in vessel border descriptors, as well as, shades, artifacts and blurred response due to ultrasound physical properties troubles automated media-adventitia segmentation. This experimental work presents a solution to such a complex problem. The process blends advanced anisotropic filtering operators and statistic classification techniques, achieving an efficient vessel border modelling strategy. First of all, we introduce the theoretic base of the method. After that, we show the steps of the algorithm, validating the method with statistics that show that the media-adventitia border detection achieves an accuracy in the range of inter-observer variability regardless of plaque nature, vessel geometry and incomplete vessel borders. Finally, we present a little Matlab application to the automatic media-adventitia border. |
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Master's thesis |
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08193 Bellaterra, Barcelona (Spain) |
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IAM; |
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IAM @ iam @ Her2005 |
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1544 |
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