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| Author | Jordina Torrents-Barrena; Aida Valls; Petia Radeva; Meritxell Arenas; Domenec Puig | ||||
| Title | Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis | Type | Book Chapter | ||
| Year | 2015 | Publication | Artificial Intelligence Research and Development | Abbreviated Journal | |
| Volume | 277 | Issue | Pages | 247 - 256 | |
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| Abstract | Breast cancer disease has recently been classified into four subtypes regarding the molecular properties of the affected tumor region. For each patient, an accurate diagnosis of the specific type is vital to decide the most appropriate therapy in order to enhance life prospects. Nowadays, advanced therapeutic diagnosis research is focused on gene selection methods, which are not robust enough. Hence, we hypothesize that computer vision algorithms can offer benefits to address the problem of discriminating among them through X-Ray images. In this paper, we propose a novel approach driven by texture feature descriptors and machine learning techniques. First, we segment the tumour part through an active contour technique and then, we perform a complete fractal analysis to collect qualitative information of the region of interest in the feature extraction stage. Finally, several supervised and unsupervised classifiers are used to perform multiclass classification of the aforementioned data. The experimental results presented in this paper support that it is possible to establish a relation between each tumor subtype and the extracted features of the patterns revealed on mammograms. | ||||
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| Publisher | IOS Press | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Frontiers in Artificial Intelligence and Applications | Abbreviated Series Title | ||
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @TVR2015 | Serial | 2780 | ||
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| Author | E. Tavalera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva | ||||
| Title | Regularized Clustering for Egocentric Video Segmentation | Type | Book Chapter | ||
| Year | 2015 | Publication | Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | Issue | Pages | 327-336 | ||
| Keywords | Temporal video segmentation ; Egocentric videos ; Clustering | ||||
| Abstract | In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energyminimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate techniques in an energy-minimization framework that serves disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. | ||||
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| Publisher | Springer International Publishing | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-319-19390-8 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @TDB2015a | Serial | 2781 | ||
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| Author | Francesco Ciompi; Simone Balocco; Juan Rigla; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | Computer-Aided Detection of Intra-Coronary Stent in Intravascular Ultrasound Sequences | Type | Journal Article | ||
| Year | 2016 | Publication | Medical Physics | Abbreviated Journal | MP |
| Volume | 43 | Issue | 10 | Pages | |
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| Abstract | Purpose: An intraluminal coronary stent is a metal mesh tube deployed in a stenotic artery during Percutaneous Coronary Intervention (PCI), in order to prevent acute vessel occlusion. The identi cation of struts location and the de nition of the stent shape are relevant for PCI planning 15 and for patient follow-up. We present a fully-automatic framework for Computer-Aided Detection
(CAD) of intra-coronary stents in Intravascular Ultrasound (IVUS) image sequences. The CAD system is able to detect stent struts and estimate the stent shape. Methods: The proposed CAD uses machine learning to provide a comprehensive interpretation of the local structure of the vessel by means of semantic classi cation. The output of the classi cation 20 stage is then used to detect struts and to estimate the stent shape. The proposed approach is validated using a multi-centric data-set of 1,015 images from 107 IVUS sequences containing both metallic and bio-absorbable stents. Results: The method was able to detect structs in both metallic stents with an overall F-measure of 77.7% and a mean distance of 0.15 mm from manually annotated struts, and in bio-absorbable 25 stents with an overall F-measure of 77.4% and a mean distance of 0.09 mm from manually annotated struts. Conclusions: The results are close to the inter-observer variability and suggest that the system has the potential of being used as method for aiding percutaneous interventions. |
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ CBR2016 | Serial | 2819 | ||
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| Author | Mariella Dimiccoli | ||||
| Title | Fundamentals of cone regression | Type | Journal | ||
| Year | 2016 | Publication | Journal of Statistics Surveys | Abbreviated Journal | |
| Volume | 10 | Issue | Pages | 53-99 | |
| Keywords | cone regression; linear complementarity problems; proximal operators. | ||||
| Abstract | Cone regression is a particular case of quadratic programming that minimizes a weighted sum of squared residuals under a set of linear inequality constraints. Several important statistical problems such as isotonic, concave regression or ANOVA under partial orderings, just to name a few, can be considered as particular instances of the cone regression problem. Given its relevance in Statistics, this paper aims to address the fundamentals of cone regression from a theoretical and practical point of view. Several formulations of the cone regression problem are considered and, focusing on the particular case of concave regression as an example, several algorithms are analyzed and compared both qualitatively and quantitatively through numerical simulations. Several improvements to enhance numerical stability and bound the computational cost are proposed. For each analyzed algorithm, the pseudo-code and its corresponding code in Matlab are provided. The results from this study demonstrate that the choice of the optimization approach strongly impacts the numerical performances. It is also shown that methods are not currently available to solve efficiently cone regression problems with large dimension (more than many thousands of points). We suggest further research to fill this gap by exploiting and adapting classical multi-scale strategy to compute an approximate solution. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1935-7516 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB; | Approved | no | ||
| Call Number | Admin @ si @Dim2016a | Serial | 2783 | ||
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| Author | Jean-Pascal Jacob; Mariella Dimiccoli; L. Moisan | ||||
| Title | Active skeleton for bacteria modelling | Type | Journal Article | ||
| Year | 2017 | Publication | Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization | Abbreviated Journal | CMBBE |
| Volume | 5 | Issue | 4 | Pages | 274-286 |
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| Abstract | The investigation of spatio-temporal dynamics of bacterial cells and their molecular components requires automated image analysis tools to track cell shape properties and molecular component locations inside the cells. In the study of bacteria aging, the molecular components of interest are protein aggregates accumulated near bacteria boundaries. This particular location makes very ambiguous the correspondence between aggregates and cells, since computing accurately bacteria boundaries in phase-contrast time-lapse imaging is a challenging task. This paper proposes an active skeleton formulation for bacteria modelling which provides several advantages: an easy computation of shape properties (perimeter, length, thickness and orientation), an improved boundary accuracy in noisy images and a natural bacteria-centred coordinate system that permits the intrinsic location of molecular components inside the cell. Starting from an initial skeleton estimate, the medial axis of the bacterium is obtained by minimising an energy function which incorporates bacteria shape constraints. Experimental results on biological images and comparative evaluation of the performances validate the proposed approach for modelling cigar-shaped bacteria like Escherichia coli. The Image-J plugin of the proposed method can be found online at http://fluobactracker.inrialpes.fr. | ||||
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| Publisher | Taylor & Francis Group | Place of Publication | Editor | ||
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| Notes | MILAB; | Approved | no | ||
| Call Number | Admin @ si @JDM2017 | Serial | 2784 | ||
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| Author | A.S. Coquel; Jean-Pascal Jacob; M. Primet; A. Demarez; Mariella Dimiccoli; T. Julou; L. Moisan; A. Lindner; H. Berry | ||||
| Title | Localization of protein aggregation in Escherichia coli is governed by diffusion and nucleoid macromolecular crowding effect | Type | Journal Article | ||
| Year | 2013 | Publication | Plos Computational Biology | Abbreviated Journal | PCB |
| Volume | 9 | Issue | 4 | Pages | |
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| Abstract | Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results provide evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3D individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion-aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of “soft” intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli. | ||||
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| Publisher | Place of Publication | Editor | : Stanislav Shvartsman, Princeton University, United States of America | ||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @CJP2013 | Serial | 2786 | ||
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| Author | Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin | ||||
| Title | Striola Magica: a functional explanation of otolith organs | Type | Journal Article | ||
| Year | 2013 | Publication | Journal of Computational Neuroscience | Abbreviated Journal | JCN |
| Volume | 35 | Issue | 2 | Pages | 125-154 |
| Keywords | Otolith organs ;Striola; Vestibular pathway | ||||
| Abstract | Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains. | ||||
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| Publisher | Springer US | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1573-6873. 2013 | ISBN | Medium | ||
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @DBG2013 | Serial | 2787 | ||
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| Author | Jose Manuel Alvarez; Theo Gevers; Antonio Lopez | ||||
| Title | Evaluating Color Representation for Online Road Detection | Type | Conference Article | ||
| Year | 2013 | Publication | ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars | Abbreviated Journal | |
| Volume | Issue | Pages | 594-595 | ||
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| Abstract | Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired using an on-board camera in different real-driving situations. |
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| Area | Expedition | Conference | CVVT:E2M | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number | Admin @ si @ AGL2013 | Serial | 2794 | ||
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| Author | Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel | ||||
| Title | An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres | Type | Book Chapter | ||
| Year | 2015 | Publication | The White Book on Public Library Network from Diputació de Barcelona | Abbreviated Journal | |
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| Notes | MV; DAG;SIAI | Approved | no | ||
| Call Number | Admin @ si @VKC2015 | Serial | 2798 | ||
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| Author | Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira | ||||
| Title | Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives | Type | Journal Article | ||
| Year | 2016 | Publication | Robotics and Autonomous Systems | Abbreviated Journal | RAS |
| Volume | 83 | Issue | Pages | 312-325 | |
| Keywords | Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives | ||||
| Abstract | When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques. | ||||
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| Publisher | Elsevier B.V. | Place of Publication | Editor | ||
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| Notes | ADAS; 600.086, 600.076 | Approved | no | ||
| Call Number | Admin @ si @OSS2016a | Serial | 2806 | ||
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| Author | Angel Sappa; P. Carvajal; Cristhian A. Aguilera-Carrasco; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla | ||||
| Title | Wavelet based visible and infrared image fusion: a comparative study | Type | Journal Article | ||
| Year | 2016 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 16 | Issue | 6 | Pages | 1-15 |
| Keywords | Image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform | ||||
| Abstract | This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR). | ||||
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| Notes | ADAS; 600.086; 600.076 | Approved | no | ||
| Call Number | Admin @ si @SCA2016 | Serial | 2807 | ||
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| Author | Angel Sappa; Cristhian A. Aguilera-Carrasco; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo | ||||
| Title | Monocular visual odometry: A cross-spectral image fusion based approach | Type | Journal Article | ||
| Year | 2016 | Publication | Robotics and Autonomous Systems | Abbreviated Journal | RAS |
| Volume | 85 | Issue | Pages | 26-36 | |
| Keywords | Monocular visual odometry; LWIR-RGB cross-spectral imaging; Image fusion | ||||
| Abstract | This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is empirically obtained by means of a mutual information based evaluation metric. The objective is to have a flexible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odometry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. | ||||
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| Publisher | Elsevier B.V. | Place of Publication | Editor | ||
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| Notes | ADAS;600.086; 600.076 | Approved | no | ||
| Call Number | Admin @ si @SAC2016 | Serial | 2811 | ||
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| Author | Alejandro Gonzalez Alzate; David Vazquez; Antonio Lopez; Jaume Amores | ||||
| Title | On-Board Object Detection: Multicue, Multimodal, and Multiview Random Forest of Local Experts | Type | Journal Article | ||
| Year | 2017 | Publication | IEEE Transactions on cybernetics | Abbreviated Journal | Cyber |
| Volume | 47 | Issue | 11 | Pages | 3980 - 3990 |
| Keywords | Multicue; multimodal; multiview; object detection | ||||
| Abstract | Despite recent significant advances, object detection continues to be an extremely challenging problem in real scenarios. In order to develop a detector that successfully operates under these conditions, it becomes critical to leverage upon multiple cues, multiple imaging modalities, and a strong multiview (MV) classifier that accounts for different object views and poses. In this paper, we provide an extensive evaluation that gives insight into how each of these aspects (multicue, multimodality, and strong MV classifier) affect accuracy both individually and when integrated together. In the multimodality component, we explore the fusion of RGB and depth maps obtained by high-definition light detection and ranging, a type of modality that is starting to receive increasing attention. As our analysis reveals, although all the aforementioned aspects significantly help in improving the accuracy, the fusion of visible spectrum and depth information allows to boost the accuracy by a much larger margin. The resulting detector not only ranks among the top best performers in the challenging KITTI benchmark, but it is built upon very simple blocks that are easy to implement and computationally efficient. | ||||
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| ISSN | 2168-2267 | ISBN | Medium | ||
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| Notes | ADAS; 600.085; 600.082; 600.076; 600.118 | Approved | no | ||
| Call Number | Admin @ si @ | Serial | 2810 | ||
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| Author | Ozan Caglayan; Walid Aransa; Adrien Bardet; Mercedes Garcia-Martinez; Fethi Bougares; Loic Barrault; Marc Masana; Luis Herranz; Joost Van de Weijer | ||||
| Title | LIUM-CVC Submissions for WMT17 Multimodal Translation Task | Type | Conference Article | ||
| Year | 2017 | Publication | 2nd Conference on Machine Translation | Abbreviated Journal | |
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| Abstract | This paper describes the monomodal and multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT17 Shared Task on Multimodal Translation. We mainly explored two multimodal architectures where either global visual features or convolutional feature maps are integrated in order to benefit from visual context. Our final systems ranked first for both En-De and En-Fr language pairs according to the automatic evaluation metrics METEOR and BLEU. | ||||
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| Area | Expedition | Conference | WMT | ||
| Notes | LAMP; 600.106; 600.120 | Approved | no | ||
| Call Number | Admin @ si @ CAB2017 | Serial | 3035 | ||
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| Author | Maria Salamo; Inmaculada Rodriguez; Maite Lopez; Anna Puig; Simone Balocco; Mariona Taule | ||||
| Title | Recurso docente para la atención de la diversidad en el aula mediante la predicción de notas | Type | Journal | ||
| Year | 2016 | Publication | ReVision | Abbreviated Journal | |
| Volume | 9 | Issue | 1 | Pages | |
| Keywords | Aprendizaje automatico; Sistema de prediccion de notas; Herramienta docente | ||||
| Abstract | Desde la implantación del Espacio Europeo de Educación Superior (EEES) en los diferentes grados, se ha puesto de manifiesto la necesidad de utilizar diversos mecanismos que permitan tratar la diversidad en el aula, evaluando automáticamente y proporcionando una retroalimentación rápida tanto al alumnado como al profesorado sobre la evolución de los alumnos en una asignatura. En este artículo se presenta la evaluación de la exactitud en las predicciones de GRADEFORESEER, un recurso docente para la predicción de notas basado en técnicas de aprendizaje automático que permite evaluar la evolución del alumnado y estimar su nota final al terminar el curso. Este recurso se ha complementado con una interfaz de usuario para el profesorado que puede ser usada en diferentes plataformas software (sistemas operativos) y en cualquier asignatura de un grado en la que se utilice evaluación continuada. Además de la descripción del recurso, este artículo presenta los resultados obtenidos al aplicar el sistema de predicción en cuatro asignaturas de disciplinas distintas: Programación I (PI), Diseño de Software (DSW) del grado de Ingeniería Informática, Tecnologías de la Información y la Comunicación (TIC) del grado de Lingüística y la asignatura Fundamentos de Tecnología (FDT) del grado de Información y Documentación, todas ellas impartidas en la Universidad de Barcelona.
La capacidad predictiva se ha evaluado de forma binaria (aprueba o no) y según un criterio de rango (suspenso, aprobado, notable o sobresaliente), obteniendo mejores predicciones en los resultados evaluados de forma binaria. |
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| Notes | MILAB; | Approved | no | ||
| Call Number | Admin @ si @ SRL2016 | Serial | 2820 | ||
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