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David Roche; Debora Gil; Jesus Giraldo |
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Multiple active receptor conformation, agonist efficacy and maximum effect of the system: the conformation-based operational model of agonism, |
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2013 |
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Drug Discovery Today |
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DDT |
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18 |
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7-8 |
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365-371 |
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The operational model of agonism assumes that the maximum effect a particular receptor system can achieve (the Em parameter) is fixed. Em estimates are above but close to the asymptotic maximum effects of endogenous agonists. The concept of Em is contradicted by superagonists and those positive allosteric modulators that significantly increase the maximum effect of endogenous agonists. An extension of the operational model is proposed that assumes that the Em parameter does not necessarily have a single value for a receptor system but has multiple values associated to multiple active receptor conformations. The model provides a mechanistic link between active receptor conformation and agonist efficacy, which can be useful for the analysis of agonist response under different receptor scenarios. |
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Elsevier |
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IAM; 600.057; 600.054 |
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IAM @ iam @ RGG2013a |
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2190 |
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Enric Marti; J. Rocarias; Petia Radeva; H. Tizon; Jordi Vitria |
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Caronte. Un gestor documental para asignaturas de universidad en el EEES |
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Miscellaneous |
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2007 |
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Desarrollo de gestion de grupos, encuestas y autoevaluacion, MoodleMoot 2007 |
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IAM;OR;MILAB;MV |
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BCNPCL @ bcnpcl @ MRR2007b |
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1128 |
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Author |
Josep Llados; Horst Bunke; Enric Marti |
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Using cyclic string matching to find rotational and reflectional symmetric shapes |
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1996 |
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Dagstuhl Seminar on Modelling and Planning for Sensor–based Intelligent Robot Systems |
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World Scientific |
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Saarbrucken (Germany). |
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R.C. Bolles, H.B.H.N. |
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DAG;IAM |
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IAM @ iam @ LBM1996 |
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1564 |
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Jaime Lopez-Krahe; Josep Llados; Enric Marti |
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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 |
Patricia Marquez |
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Title |
Conditions Ensuring Accuracy of Local Optical Flow Schemes |
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2010 |
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CVC Tehcnical Report |
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157 |
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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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Master's thesis |
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Bellaterra 08193, Barcelona, Spain |
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IAM; |
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IAM @ iam @ Mar2010 |
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1582 |
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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 |
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142 |
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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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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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Bellaterra 08193, Barcelona, Spain |
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IAM; |
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IAM @ iam @ And2009 |
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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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2004 |
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CVC Technical Report |
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78 |
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Cardiac Analysis; Deformable Models; Active Contour Models; Active Shape Models; Tagged MRI; HARP; Contrast Echocardiography. |
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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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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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Debora Gil; Petia Radeva |
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Curvature based Distance Maps |
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2003 |
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CVC Technical Report |
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70 |
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Computer Vision Center |
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IAM;MILAB |
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IAM @ iam @ GIR2003a |
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1534 |
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Author |
Aura Hernandez-Sabate |
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Automatic adventitia segmentation in IntraVascular UltraSound images |
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2005 |
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CVC Technical Report |
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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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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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