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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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Bellaterra 08193, Barcelona, Spain |
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IAM @ iam @ Mar2010 |
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1582 |
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Sergio Vera |
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Title |
Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis |
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2010 |
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CVC Technical Report |
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164 |
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Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score |
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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. |
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Bellaterra 01893, Barcelona, Spain |
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IAM @ iam @ Ver2010 |
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1661 |
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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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2011 |
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CVC Technical Report |
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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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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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Bellaterra (Barcelona) |
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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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2011 |
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CVC Technical Report |
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168 |
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Bronchoscopy, tracheal ring, segmentation |
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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 |
David Roche; Debora Gil; Jesus Giraldo |
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Mechanistic analysis of the function of agonists and allosteric modulators: Reconciling two-state and operational models |
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2013 |
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British Journal of Pharmacology |
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BJP |
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169 |
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6 |
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1189-202 |
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Two-state and operational models of both agonism and allosterism are compared to identify and characterize common pharmacological parameters. To account for the receptor-dependent basal response, constitutive receptor activity is considered in the operational models. By arranging two-state models as the fraction of active receptors and operational models as the fractional response relative to the maximum effect of the system, a one-by-one correspondence between parameters is found. The comparative analysis allows a better understanding of complex allosteric interactions. In particular, the inclusion of constitutive receptor activity in the operational model of allosterism allows the characterization of modulators able to lower the basal response of the system; that is, allosteric modulators with negative intrinsic efficacy. Theoretical simulations and overall goodness of fit of the models to simulated data suggest that it is feasible to apply the models to experimental data and constitute one step forward in receptor theory formalism. |
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IAM; 600.044; 605.203 |
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IAM @ iam @ RGG2013b |
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2195 |
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Author |
Francesco Brughi |
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Title |
Artistic Heritage Motive Retrieval: an Explorative Study |
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2013 |
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CVC Technical Report |
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176 |
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Admin @ si @ Bru2013 |
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2410 |
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Antonio Esteban Lansaque |
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3D reconstruction and recognition using structured ligth |
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2014 |
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CVC Technical Report |
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179 |
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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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UAB; September 2014 |
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IAM; 600.075 |
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Admin @ si @ Est2014 |
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2578 |
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Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil |
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BronchoPose: an analysis of data and model configuration for vision-based bronchoscopy pose estimation |
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2023 |
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Computer Methods and Programs in Biomedicine |
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CMPB |
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228 |
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107241 |
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Videobronchoscopy guiding; Deep learning; Architecture optimization; Datasets; Standardized evaluation framework; Pose estimation |
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Vision-based bronchoscopy (VB) models require the registration of the virtual lung model with the frames from the video bronchoscopy to provide effective guidance during the biopsy. The registration can be achieved by either tracking the position and orientation of the bronchoscopy camera or by calibrating its deviation from the pose (position and orientation) simulated in the virtual lung model. Recent advances in neural networks and temporal image processing have provided new opportunities for guided bronchoscopy. However, such progress has been hindered by the lack of comparative experimental conditions.
In the present paper, we share a novel synthetic dataset allowing for a fair comparison of methods. Moreover, this paper investigates several neural network architectures for the learning of temporal information at different levels of subject personalization. In order to improve orientation measurement, we also present a standardized comparison framework and a novel metric for camera orientation learning. Results on the dataset show that the proposed metric and architectures, as well as the standardized conditions, provide notable improvements to current state-of-the-art camera pose estimation in video bronchoscopy. |
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Elsevier |
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Admin @ si @ BSC2023 |
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3702 |
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Marta Ligero; Alonso Garcia Ruiz; Cristina Viaplana; Guillermo Villacampa; Maria V Raciti; Jaid Landa; Ignacio Matos; Juan Martin Liberal; Maria Ochoa de Olza; Cinta Hierro; Joaquin Mateo; Macarena Gonzalez; Rafael Morales Barrera; Cristina Suarez; Jordi Rodon; Elena Elez; Irene Braña; Eva Muñoz-Couselo; Ana Oaknin; Roberta Fasani; Paolo Nuciforo; Debora Gil; Carlota Rubio Perez; Joan Seoane; Enriqueta Felip; Manuel Escobar; Josep Tabernero; Joan Carles; Rodrigo Dienstmann; Elena Garralda; Raquel Perez Lopez |
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A CT-based radiomics signature is associated with response to immune checkpoint inhibitors in advanced solid tumors |
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2021 |
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Radiology |
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299 |
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1 |
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109-119 |
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Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue. |
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IAM; 600.145 |
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Admin @ si @ LGV2021 |
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3593 |
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Jose Elias Yauri; Aura Hernandez-Sabate; Pau Folch; Debora Gil |
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Mental Workload Detection Based on EEG Analysis |
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2021 |
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Artificial Intelligent Research and Development. Proceedings 23rd International Conference of the Catalan Association for Artificial Intelligence. |
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339 |
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268-277 |
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Cognitive states; Mental workload; EEG analysis; Neural Networks. |
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The study of mental workload becomes essential for human work efficiency, health conditions and to avoid accidents, since workload compromises both performance and awareness. Although workload has been widely studied using several physiological measures, minimising the sensor network as much as possible remains both a challenge and a requirement.
Electroencephalogram (EEG) signals have shown a high correlation to specific cognitive and mental states like workload. However, there is not enough evidence in the literature to validate how well models generalize in case of new subjects performing tasks of a workload similar to the ones included during model’s training.
In this paper we propose a binary neural network to classify EEG features across different mental workloads. Two workloads, low and medium, are induced using two variants of the N-Back Test. The proposed model was validated in a dataset collected from 16 subjects and shown a high level of generalization capability: model reported an average recall of 81.81% in a leave-one-out subject evaluation. |
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Virtual; October 20-22 2021 |
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CCIA |
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IAM; 600.139; 600.118; 600.145 |
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