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Author |
Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru |
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Title |
Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs |
Type |
Conference Article |
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Year |
2011 |
Publication |
Workshop on Computational and Clinical Applications in Abdominal Imaging |
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Volume |
7029 |
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Pages |
223-230 |
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Abstract  |
Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations. |
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Nice, France |
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Springer Berlin Heidelberg |
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In H. Yoshida et al |
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ABDI |
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IAM; MV |
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no |
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Call Number |
VGB2011 |
Serial |
2036 |
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Author |
Debora Gil; Sergio Vera; Agnes Borras; Albert Andaluz; Miguel Angel Gonzalez Ballester |
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Title |
Anatomical Medial Surfaces with Efficient Resolution of Branches Singularities |
Type |
Journal Article |
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Year |
2017 |
Publication |
Medical Image Analysis |
Abbreviated Journal |
MIA |
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Volume |
35 |
Issue |
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Pages |
390-402 |
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Keywords |
Medial Representations; Shape Recognition; Medial Branching Stability ; Singular Points |
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Abstract |
Medial surfaces are powerful tools for shape description, but their use has been limited due to the sensibility existing methods to branching artifacts. Medial branching artifacts are associated to perturbations of the object boundary rather than to geometric features. Such instability is a main obstacle for a con dent application in shape recognition and description. Medial branches correspond to singularities of the medial surface and, thus, they are problematic for existing morphological and energy-based algorithms. In this paper, we use algebraic geometry concepts in an energy-based approach to compute a medial surface presenting a stable branching topology. We also present an ecient GPU-CPU implementation using standard image processing tools. We show the method computational eciency and quality on a custom made synthetic database. Finally, we present some results on a medical imaging application for localization of abdominal pathologies. |
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Elsevier B.V. |
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IAM; 600.060; 600.096; 600.075; 600.145 |
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Admin @ si @ GVB2017 |
Serial |
2775 |
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Author |
Debora Gil |
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Title |
Geometric Differential Operators for Shape Modelling |
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Book Whole |
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Year |
2004 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Medical imaging feeds research in many computer vision and image processing fields: image filtering, segmentation, shape recovery, registration, retrieval and pattern matching. Because of their low contrast changes and large variety of artifacts and noise, medical imaging processing techniques relying on an analysis of the geometry of image level sets rather than on intensity values result in more robust treatment. From the starting point of treatment of intravascular images, this PhD thesis ad- dresses the design of differential image operators based on geometric principles for a robust shape modelling and restoration. Among all fields applying shape recovery, we approach filtering and segmentation of image objects. For a successful use in real images, the segmentation process should go through three stages: noise removing, shape modelling and shape recovery. This PhD addresses all three topics, but for the sake of algorithms as automated as possible, techniques for image processing will be designed to satisfy three main principles: a) convergence of the iterative schemes to non-trivial states avoiding image degeneration to a constant image and representing smooth models of the originals; b) smooth asymptotic behav- ior ensuring stabilization of the iterative process; c) fixed parameter values ensuring equal (domain free) performance of the algorithms whatever initial images/shapes. Our geometric approach to the generic equations that model the different processes approached enables defining techniques satisfying all the former requirements. First, we introduce a new curvature-based geometric flow for image filtering achieving a good compromise between noise removing and resemblance to original images. Sec- ond, we describe a new family of diffusion operators that restrict their scope to image level curves and serve to restore smooth closed models from unconnected sets of points. Finally, we design a regularization of snake (distance) maps that ensures its smooth convergence towards any closed shape. Experiments show that performance of the techniques proposed overpasses that of state-of-the-art algorithms. |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
Barcelona (Spain) |
Editor |
Jordi Saludes i Closa;Petia Radeva |
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84-933652-0-3 |
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prit |
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IAM; |
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Call Number |
IAM @ iam @ GIL2004 |
Serial |
1517 |
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Author |
Debora Gil; Aura Hernandez-Sabate; Julien Enconniere; Saryani Asmayawati; Pau Folch; Juan Borrego-Carazo; Miquel Angel Piera |
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Title |
E-Pilots: A System to Predict Hard Landing During the Approach Phase of Commercial Flights |
Type |
Journal Article |
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Year |
2022 |
Publication |
IEEE Access |
Abbreviated Journal |
ACCESS |
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Volume |
10 |
Issue |
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Pages |
7489-7503 |
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Abstract |
More than half of all commercial aircraft operation accidents could have been prevented by executing a go-around. Making timely decision to execute a go-around manoeuvre can potentially reduce overall aviation industry accident rate. In this paper, we describe a cockpit-deployable machine learning system to support flight crew go-around decision-making based on the prediction of a hard landing event.
This work presents a hybrid approach for hard landing prediction that uses features modelling temporal dependencies of aircraft variables as inputs to a neural network. Based on a large dataset of 58177 commercial flights, the results show that our approach has 85% of average sensitivity with 74% of average specificity at the go-around point. It follows that our approach is a cockpit-deployable recommendation system that outperforms existing approaches. |
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Notes |
IAM; 600.139; 600.118; 600.145 |
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no |
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Call Number |
Admin @ si @ GHE2022 |
Serial |
3721 |
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Author |
Albert Andaluz; Francesc Carreras; Cristina Santa Marta;Debora Gil |
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Title |
Myocardial torsion estimation with Tagged-MRI in the OsiriX platform |
Type |
Conference Article |
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Year |
2012 |
Publication |
ISBI Workshop on Open Source Medical Image Analysis software |
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Abstract |
Myocardial torsion (MT) plays a crucial role in the assessment of the functionality of the
left ventricle. For this purpose, the IAM group at the CVC has developed the Harmonic Phase Flow (HPF) plugin for the Osirix DICOM platform . We have validated its funcionalty on sequences acquired using different protocols and including healthy and pathological cases. Results show similar torsion trends for SPAMM acquisitions, with pathological cases introducing expected deviations from the ground truth. Finally, we provide the plugin free of charge at http://iam.cvc.uab.es |
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Barcelona, Spain |
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IEEE |
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Editor |
Wiro Niessen (Erasmus MC) and Marc Modat (UCL) |
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ISBI |
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IAM |
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IAM @ iam @ ACS2012 |
Serial |
1900 |
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Author |
David Castells; Vinh Ngo; Juan Borrego-Carazo; Marc Codina; Carles Sanchez; Debora Gil; Jordi Carrabina |
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Title |
A Survey of FPGA-Based Vision Systems for Autonomous Cars |
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Journal Article |
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Year |
2022 |
Publication |
IEEE Access |
Abbreviated Journal |
ACESS |
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Volume |
10 |
Issue |
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Pages |
132525-132563 |
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Keywords |
Autonomous automobile; Computer vision; field programmable gate arrays; reconfigurable architectures |
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Abstract |
On the road to making self-driving cars a reality, academic and industrial researchers are working hard to continue to increase safety while meeting technical and regulatory constraints Understanding the surrounding environment is a fundamental task in self-driving cars. It requires combining complex computer vision algorithms. Although state-of-the-art algorithms achieve good accuracy, their implementations often require powerful computing platforms with high power consumption. In some cases, the processing speed does not meet real-time constraints. FPGA platforms are often used to implement a category of latency-critical algorithms that demand maximum performance and energy efficiency. Since self-driving car computer vision functions fall into this category, one could expect to see a wide adoption of FPGAs in autonomous cars. In this paper, we survey the computer vision FPGA-based works from the literature targeting automotive applications over the last decade. Based on the survey, we identify the strengths and weaknesses of FPGAs in this domain and future research opportunities and challenges. |
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16 December 2022 |
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IEEE |
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IAM; 600.166 |
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no |
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Call Number |
Admin @ si @ CNB2022 |
Serial |
3760 |
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Author |
Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate |
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Title |
Local Analysis of Confidence Measures for Optical Flow Quality Evaluation |
Type |
Conference Article |
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Year |
2014 |
Publication |
9th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
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3 |
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Pages |
450-457 |
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Keywords |
Optical Flow; Confidence Measure; Performance Evaluation. |
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Abstract |
Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance. |
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Lisboa; January 2014 |
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VISAPP |
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IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 |
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Call Number |
Admin @ si @ MGM2014 |
Serial |
2432 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
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Conference Article |
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2011 |
Publication |
IEEE International Conference on Computer Vision – Workshops |
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2042-2049 |
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IEEE International Conference on Computer Vision – Workshops |
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Abstract |
Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
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IEEE |
Place of Publication |
Barcelona (Spain) |
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English |
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English |
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ICCVW |
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IAM; ADAS |
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no |
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IAM @ iam @ MGH2011 |
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1682 |
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Author |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
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Conference Article |
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2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
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7324 |
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I |
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184-191 |
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Keywords |
Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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Abstract |
Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures. |
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Aveiro, Portugal |
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Springer-Verlag Berlin Heidelberg |
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english |
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Campilho, Aurélio and Kamel, Mohamed |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-31294-6 |
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ICIAR |
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IAM |
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IAM @ iam @ MGH2012a |
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1899 |
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Author |
Oriol Ramos Terrades; Albert Berenguel; Debora Gil |
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Title |
A Flexible Outlier Detector Based on a Topology Given by Graph Communities |
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Journal Article |
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2022 |
Publication |
Big Data Research |
Abbreviated Journal |
BDR |
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29 |
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100332 |
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Keywords |
Classification algorithms; Detection algorithms; Description of feature space local structure; Graph communities; Machine learning algorithms; Outlier detectors |
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Abstract |
Outlier detection is essential for optimal performance of machine learning methods and statistical predictive models. Their detection is especially determinant in small sample size unbalanced problems, since in such settings outliers become highly influential and significantly bias models. This particular experimental settings are usual in medical applications, like diagnosis of rare pathologies, outcome of experimental personalized treatments or pandemic emergencies. In contrast to population-based methods, neighborhood based local approaches compute an outlier score from the neighbors of each sample, are simple flexible methods that have the potential to perform well in small sample size unbalanced problems. A main concern of local approaches is the impact that the computation of each sample neighborhood has on the method performance. Most approaches use a distance in the feature space to define a single neighborhood that requires careful selection of several parameters, like the number of neighbors.
This work presents a local approach based on a local measure of the heterogeneity of sample labels in the feature space considered as a topological manifold. Topology is computed using the communities of a weighted graph codifying mutual nearest neighbors in the feature space. This way, we provide with a set of multiple neighborhoods able to describe the structure of complex spaces without parameter fine tuning. The extensive experiments on real-world and synthetic data sets show that our approach outperforms, both, local and global strategies in multi and single view settings. |
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August 28, 2022 |
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DAG; IAM; 600.140; 600.121; 600.139; 600.145; 600.159 |
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Admin @ si @ RBG2022a |
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3718 |
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Oriol Ramos Terrades; Albert Berenguel; Debora Gil |
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A flexible outlier detector based on a topology given by graph communities |
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Miscellaneous |
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2020 |
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Arxiv |
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Outlier, or anomaly, detection is essential for optimal performance of machine learning methods and statistical predictive models. It is not just a technical step in a data cleaning process but a key topic in many fields such as fraudulent document detection, in medical applications and assisted diagnosis systems or detecting security threats. In contrast to population-based methods, neighborhood based local approaches are simple flexible methods that have the potential to perform well in small sample size unbalanced problems. However, a main concern of local approaches is the impact that the computation of each sample neighborhood has on the method performance. Most approaches use a distance in the feature space to define a single neighborhood that requires careful selection of several parameters. This work presents a local approach based on a local measure of the heterogeneity of sample labels in the feature space considered as a topological manifold. Topology is computed using the communities of a weighted graph codifying mutual nearest neighbors in the feature space. This way, we provide with a set of multiple neighborhoods able to describe the structure of complex spaces without parameter fine tuning. The extensive experiments on real-world data sets show that our approach overall outperforms, both, local and global strategies in multi and single view settings. |
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IAM; DAG; 600.139; 600.145; 600.140; 600.121 |
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Admin @ si @ RBG2020 |
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3475 |
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Author |
Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez |
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Title |
Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules |
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Conference Article |
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2023 |
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37th International Congress and Exhibition is organized by Computer Assisted Radiology and Surgery |
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Pòster |
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Munich; Germany; June 2023 |
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CARS |
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IAM |
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Admin @ si @ TGR2023a |
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3950 |
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Sonia Baeza; Debora Gil; Carles Sanchez; Guillermo Torres; Ignasi Garcia Olive; Ignasi Guasch; Samuel Garcia Reina; Felipe Andreo; Jose Luis Mate; Jose Luis Vercher; Antonio Rosell |
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Title |
Biopsia virtual radiomica para el diagnóstico histológico de nódulos pulmonares – Resultados intermedios del proyecto Radiolung |
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Conference Article |
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Year |
2023 |
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SEPAR |
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Address |
Granada; Spain; June 2023 |
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Notes |
IAM |
Approved |
no |
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Call Number |
Admin @ si @ BGS2023 |
Serial |
3951 |
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| Permanent link to this record |
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Author |
Debora Gil; Guillermo Torres; Carles Sanchez |
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Title |
Transforming radiomic features into radiological words |
Type |
Conference Article |
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Year |
2023 |
Publication |
IEEE International Symposium on Biomedical Imaging |
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Address |
Cartagena de Indias; Colombia; April 2023 |
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ISBI |
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IAM |
Approved |
no |
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Call Number |
Admin @ si @ GTS2023 |
Serial |
3952 |
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| Permanent link to this record |
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Author |
Guillermo Torres; Debora Gil; Antonio Rosell; Sonia Baeza; Carles Sanchez |
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Title |
A radiomic biopsy for virtual histology of pulmonary nodules |
Type |
Conference Article |
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Year |
2023 |
Publication |
IEEE International Symposium on Biomedical Imaging |
Abbreviated Journal |
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Volume |
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Address |
Cartagena de Indias; Colombia; April 2023 |
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ISBI |
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Notes |
IAM |
Approved |
no |
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Call Number |
Admin @ si @ TGR2023b |
Serial |
3954 |
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| Permanent link to this record |
