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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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Miscellaneous |
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Year |
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 |
Teresa Moran; Vanesa Quiroga; Beatriz Cirauqui; Laia Vila; Maria Gil-Moreno; Enric Carcereny; Mireia Margeli; Ana Muñoz-Marmol; Jose Luis Mate; Jose Maria Velarde; Miguel Angel Molina; Rafael Rosell |


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Title |
A Single-Center Retrospective Study of Patients with Double Primary Cancers: Breast Cancer and EGFR-Mutant Non-Small Cell Lung Cancer |
Type |
Journal Article |
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Year |
2019 |
Publication |
Oncology Research and Treatment |
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Volume |
42 |
Issue |
3 |
Pages |
107-114 |
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Abstract |
Background: Second primary malignancies (SPM) in the lung are not common in breast cancer (BC) patients. EGFR-mutant lung cancer (LC) is a separate molecular subset, and the co-existence of EGFR-mutant LC and BC has not been explored. We hypothesized that EGFR-mutant LC patients could have higher rates of primary BC than those with EGFR-wild type (WT).
Methods: We collected data on clinical and molecular characteristics and outcomes of female patients with LC and a previous or simultaneous history of primary BC treated in our hospital from 2008 to 2014.
Results: Data on treatment, follow-up, and EGFR mutation status were available for 356 patients. 17.7% (11/62) of patients with EGFR mutations had BC, compared to 1.02% (3/294) of EGFR-WT patients (p < 0.001). Both tumors were metachronous in 81.8%, with LC diagnosed 9 years after the diagnosis of BC. 5 of the 6 (83.3%) BC patients treated with radiotherapy developed LC in an area within the radiation field. No EGFR mutations were detected in BC tissue and no HER2 expression was detected in LC samples.
Conclusion: SPM in the lung and breast occur more frequently among EGFR-mutant compared to EGFR-WT LC patients. Radiotherapy for BC may increase the risk of developing primary LC. |
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IAM; 600.139; 600.145 |
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Admin @ si @ MQC2019 |
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3476 |
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Author |
Esmitt Ramirez; Carles Sanchez; Debora Gil |


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Title |
Localizing Pulmonary Lesions Using Fuzzy Deep Learning |
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Conference Article |
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Year |
2019 |
Publication |
21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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290-294 |
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The usage of medical images is part of the clinical daily in several healthcare centers around the world. Particularly, Computer Tomography (CT) images are an important key in the early detection of suspicious lung lesions. The CT image exploration allows the detection of lung lesions before any invasive procedure (e.g. bronchoscopy, biopsy). The effective localization of lesions is performed using different image processing and computer vision techniques. Lately, the usage of deep learning models into medical imaging from detection to prediction shown that is a powerful tool for Computer-aided software. In this paper, we present an approach to localize pulmonary lung lesion using fuzzy deep learning. Our approach uses a simple convolutional neural network based using the LIDC-IDRI dataset. Each image is divided into patches associated a probability vector (fuzzy) according their belonging to anatomical structures on a CT. We showcase our approach as part of a full CAD system to exploration, planning, guiding and detection of pulmonary lesions. |
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Timisoara; Rumania; September 2019 |
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SYNASC |
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IAM; 600.145; 600.140; 601.337; 601.323 |
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no |
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Call Number |
Admin @ si @ RSG2019 |
Serial |
3531 |
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Author |
Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil |



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Title |
An illumination model of the trachea appearance in videobronchoscopy images |
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Book Chapter |
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Year |
2012 |
Publication |
Image Analysis and Recognition |
Abbreviated Journal |
LNCS |
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Volume |
7325 |
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313-320 |
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Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation |
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Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution. |
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Aveiro, Portugal |
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Springer Berlin Heidelberg |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-31297-7 |
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800 |
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ICIAR |
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MV;IAM |
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no |
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Call Number |
IAM @ iam @ SSR2012 |
Serial |
1898 |
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Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |


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Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
Type |
Conference Article |
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Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
Abbreviated Journal |
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8361 |
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31-38 |
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Lumen centre detection; Bronchoscopy; Colonoscopy |
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We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). |
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Nagoya; Japan; September 2013 |
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Springer International Publishing |
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Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus |
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LNCS |
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978-3-319-05665-4 |
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800 |
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CLIP |
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MV; IAM; 600.047; 600.044; 600.060 |
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Admin @ si @ SBG2013 |
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2302 |
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Author |
Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez |


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Title |
Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance |
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Conference Article |
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2013 |
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Proceedings of the International Conference on Computer Vision Theory and Applications |
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1 |
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153--161 |
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Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model |
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Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability |
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Barcelona; February 2013 |
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SciTePress |
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Portugal |
Editor |
Sebastiano Battiato and José Braz |
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LNCS |
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978-989-8565-47-1 |
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800 |
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VISAPP |
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IAM;MV; 600.044; 600.047; 600.060; 605.203 |
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IAM @ iam @ SGR2013 |
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2123 |
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Author |
Joan M. Nuñez; Debora Gil; Fernando Vilariño |

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Finger joint characterization from X-ray images for rheymatoid arthritis assessment |
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Conference Article |
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2013 |
Publication |
6th International Conference on Biomedical Electronics and Devices |
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288-292 |
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Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde |
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In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection. |
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Barcelona; February 2013 |
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SciTePress |
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800 |
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BIODEVICES |
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IAM;MV; 600.057; 600.054 |
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IAM @ iam @ NGV2013 |
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2196 |
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Author |
Ole Larsen; Petia Radeva; Enric Marti |

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Title |
Calculating the Bounds on the Optimal Parameters of Elasticity for a Snake |
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Report |
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1994 |
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Technical Report |
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Aalborg University |
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Aalborg University, Laboratory of image Analysis. |
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Denmark |
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Aalborg University, Laboratory of image Analysis. |
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MILAB;IAM |
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IAM @ iam @ LRM1994 |
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1560 |
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Author |
Enric Marti; Petia Radeva; Ricardo Toledo; Jordi Vitria |

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Experiencia de aplicación de la metodología de aprendizaje por proyectos en asignaturas de Ingeniería Informática para una mejor adaptación a los créditos ECTS i al Espacio Europeo de Educación Superior |
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Miscellaneous |
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2005 |
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Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR) |
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Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR) |
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IAM;RV;OR;MILAB;ADAS;MV |
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IAM @ iam @ MRT2005 |
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1608 |
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Author |
Fernando Vilariño; Enric Marti |

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Title |
New didactic techniques in the EHES applying mobile technologies |
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Miscellaneous |
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2008 |
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Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya |
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Agencia de Gestió d’Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya |
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Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya |
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MILAB;IAM;MV; |
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no |
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Call Number |
IAM @ iam @ VIM2008 |
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1664 |
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