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Eric Amiel. (2005). "Visualisation de vaisseaux sanguins " (Enric Marti, Ed.). Bachelor's thesis, Université Paul Sabatier Toulouse III, Toulouse.
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Albert Andaluz. (2009). "LV Contour Segmentation in TMR images using Semantic Description of Tissue and Prior Knowledge Correction " (Vol. 142). Master's thesis, , Bellaterra 08193, Barcelona, Spain.
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.
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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Ferran Poveda. (2009). "Visualització i interpretació tridimensional de l’arquitectura de les fibres musculars del miocardi ". Master's thesis, , 08193 Bellaterra, Barcelona (Spain).
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Patricia Marquez. (2010). "Conditions Ensuring Accuracy of Local Optical Flow Schemes " (Vol. 157). Master's thesis, , Bellaterra 08193, Barcelona, Spain.
Abstract: Accurate computation of optical flow is a key-point in many image processing fields. Detection of anomalous and unpredicted agents (such as pedestrians, bikers or cars) in urban scenes or pathology discrimination in medical imaging sequences, to mention just a two. The above kinds sequences present two main difficulties for standard optical flow techniques. On one hand, variability in acquisition conditions (illuminance, medical imaging modality, ...) force an alterantive representation for images fulfilling the britghtness constancy constrain. On the hand, current variational schemes produce oversmoothed fields unable to properly model discontinuous behaviours such as collisions or functionless pathological areas. This master project explores the abilities and limitations of local and global optical flow approaches. The master student will put especial emphasis in the theoretical grounds behind in order to design a variational framework combining the theoretical advantages of the considered techniques. In particular an optical flow based on Gabor phase tracking (developed in the group for medical imaging) will be generalized to urban scenes.
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Sergio Vera. (2010). "Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis " (Vol. 164). Master's thesis, , Bellaterra 01893, Barcelona, Spain.
Abstract: Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research.
Keywords: Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score
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Joan M. Nuñez. (2011). "Computer vision techniques for characterization of finger joints in X-ray image " (Dr. Fernando Vilariño and Dra. Debora Gil, Ed.) (Vol. 165). Master's thesis, , .
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
Keywords: Rheumatoid arthritis, X-ray, Sharp Van der Heijde, joint characterization, sclerosis detection, bone detection, edge, ridge
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Carles Sanchez. (2011). "Tracheal ring detection in bronchoscopy " (F. J. S. Debora Gil, Ed.) (Vol. 168). Master's thesis, , .
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.
Keywords: Bronchoscopy, tracheal ring, segmentation
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Francesco Brughi. (2013)." Artistic Heritage Motive Retrieval: an Explorative Study" (Vol. 176). Master's thesis, , .
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Antonio Esteban Lansaque. (2014)." 3D reconstruction and recognition using structured ligth" (Vol. 179). Master's thesis, , .
Abstract: This work covers the problem of 3D reconstruction, recognition and 6DOF pose estimation. The goal of this project is to reconstruct a 3D scene and to align an object model of the industrial pieces onto the reconstructed scene. The reconstruction algorithm is based on stereo techniques and the recognition algorithm is based on SHOT descriptors computed on a set of uniform keypoints. Correspondences are used to estimate a first 6DOF transformation that maps the model onto the scene and then ICP algorithm is used to refine the transformation. In order to check the effectiveness of the proposed algorithm, several experiments were performed. These experiments were conducted on a lab environment in order to get results under the same conditions in all of them. Although obtained results are not real time results, the proposed algorithm ends up with high rates of object recognition.
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