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Author Gemma Sanchez; Josep Llados; Enric Marti edit  url
openurl 
  Title Segmentation and analysis of linial texture in plans Type Conference Article
  Year 1997 Publication Intelligence Artificielle et Complexité. Abbreviated Journal  
  Volume Issue Pages  
  Keywords Structural Texture, Voronoi, Hierarchical Clustering, String Matching.  
  Abstract The problem of texture segmentation and interpretation is one of the main concerns in the field of document analysis. Graphical documents often contain areas characterized by a structural texture whose recognition allows both the document understanding, and its storage in a more compact way. In this work, we focus on structural linial textures of regular repetition contained in plan documents. Starting from an atributed graph which represents the vectorized input image, we develop a method to segment textured areas and recognize their placement rules. We wish to emphasize that the searched textures do not follow a predefined pattern. Minimal closed loops of the input graph are computed, and then hierarchically clustered. In this hierarchical clustering, a distance function between two closed loops is defined in terms of their areas difference and boundary resemblance computed by a string matching procedure. Finally it is noted that, when the texture consists of isolated primitive elements, the same method can be used after computing a Voronoi Tesselation of the input graph.  
  Address Paris, France  
  Corporate Author Thesis  
  Publisher Place of Publication Paris Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference AERFAI  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ SLM1997 Serial 1649  
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Author Debora Gil; Agnes Borras; Manuel Ballester; Francesc Carreras; Ruth Aris; Manuel Vazquez; Enric Marti; Ferran Poveda edit   pdf
url  doi
isbn  openurl
  Title MIOCARDIA: Integrating cardiac function and muscular architecture for a better diagnosis Type Conference Article
  Year 2011 Publication 14th International Symposium on Applied Sciences in Biomedical and Communication Technologies Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. The MIOCARDIA project is a multidisciplinary project in cooperation with l'Hospital de la Santa Creu i de Sant Pau, Clinica la Creu Blanca and Barcelona Supercomputing Center. The ultimate goal of this project is defining a computational model of the myocardium. The model takes into account the deep interrelation between the anatomy and the mechanics of the heart. The paper explains the workflow of the MIOCARDIA project. It also introduces a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and provides evidences of a global helical organization.  
  Address Barcelona; Spain  
  Corporate Author Association for Computing Machinery Thesis  
  Publisher Place of Publication Barcelona, Spain Editor Association for Computing Machinery  
  Language english Summary Language english Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-0913-4 Medium  
  Area Expedition Conference ISABEL  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGB2011 Serial 1691  
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Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
url  openurl
  Title Assessing agonist efficacy in an uncertain Em world Type Conference Article
  Year 2012 Publication 40th Keystone Symposia on mollecular and celular biology Abbreviated Journal  
  Volume Issue Pages 79  
  Keywords  
  Abstract The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed.
 
  Address Fairmont Banff Springs, Banff, Alberta, Canada  
  Corporate Author Keystone Symposia Thesis  
  Publisher Keystone Symposia Place of Publication Editor A. Christopoulus and M. Bouvier  
  Language english Summary Language english Original Title  
  Series Editor Keystone Symposia Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference KSMCB  
  Notes IAM Approved no  
  Call Number IAM @ iam @ RGG2012 Serial 1855  
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti edit  url
isbn  openurl
  Title A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa Type Conference Article
  Year 2003 Publication Proceedings of Pattern Recognition in Information Systems Abbreviated Journal  
  Volume Issue Pages 1-13  
  Keywords  
  Abstract  
  Address Angers, France  
  Corporate Author Thesis  
  Publisher ICEIS Press Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 972-98816-3-4 Medium  
  Area Expedition Conference PRIS'03  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LVS2003 Serial 1576  
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Author Gloria Fernandez-Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; H.Cordova; Cristina Sanchez-Montes; I.Araujo ; Maria Lopez-Ceron; J.Llach; F. Javier Sanchez edit   pdf
url  openurl
  Title Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps Type Conference Article
  Year 2015 Publication Proceedings of 23 United European- UEG Week 2015 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference UEG  
  Notes MV; IAM; 600.075;SIAI Approved no  
  Call Number Admin @ si @ FBR2015 Serial 2732  
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Author Debora Gil; Antonio Esteban Lansaque; Sebastian Stefaniga; Mihail Gaianu; Carles Sanchez edit   pdf
url  openurl
  Title Data Augmentation from Sketch Type Conference Article
  Year 2019 Publication International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging Abbreviated Journal  
  Volume 11840 Issue Pages 155-162  
  Keywords Data augmentation; cycleGANs; Multi-objective optimization  
  Abstract State of the art machine learning methods need huge amounts of data with unambiguous annotations for their training. In the context of medical imaging this is, in general, a very difficult task due to limited access to clinical data, the time required for manual annotations and variability across experts. Simulated data could serve for data augmentation provided that its appearance was comparable to the actual appearance of intra-operative acquisitions. Generative Adversarial Networks (GANs) are a powerful tool for artistic style transfer, but lack a criteria for selecting epochs ensuring also preservation of intra-operative content.

We propose a multi-objective optimization strategy for a selection of cycleGAN epochs ensuring a mapping between virtual images and the intra-operative domain preserving anatomical content. Our approach has been applied to simulate intra-operative bronchoscopic videos and chest CT scans from virtual sketches generated using simple graphical primitives.
 
  Address Shenzhen; China; October 2019  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CLIP  
  Notes IAM; 600.145; 601.337; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ GES2019 Serial 3359  
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Author Esmitt Ramirez; Carles Sanchez; Debora Gil edit   pdf
url  doi
openurl 
  Title Localizing Pulmonary Lesions Using Fuzzy Deep Learning Type Conference Article
  Year 2019 Publication 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages 290-294  
  Keywords  
  Abstract 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.  
  Address Timisoara; Rumania; September 2019  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference SYNASC  
  Notes IAM; 600.145; 600.140; 601.337; 601.323 Approved no  
  Call Number Admin @ si @ RSG2019 Serial 3531  
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Author Carles Sanchez; Miguel Viñas; Coen Antens; Agnes Borras; Debora Gil edit   pdf
url  doi
openurl 
  Title Back to Front Architecture for Diagnosis as a Service Type Conference Article
  Year 2018 Publication 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages 343-346  
  Keywords  
  Abstract Software as a Service (SaaS) is a cloud computing model in which a provider hosts applications in a server that customers use via internet. Since SaaS does not require to install applications on customers' own computers, it allows the use by multiple users of highly specialized software without extra expenses for hardware acquisition or licensing. A SaaS tailored for clinical needs not only would alleviate licensing costs, but also would facilitate easy access to new methods for diagnosis assistance. This paper presents a SaaS client-server architecture for Diagnosis as a Service (DaaS). The server is based on docker technology in order to allow execution of softwares implemented in different languages with the highest portability and scalability. The client is a content management system allowing the design of websites with multimedia content and interactive visualization of results allowing user editing. We explain a usage case that uses our DaaS as crowdsourcing platform in a multicentric pilot study carried out to evaluate the clinical benefits of a software for assessment of central airway obstruction.  
  Address Timisoara; Rumania; September 2018  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference SYNASC  
  Notes IAM; 600.145 Approved no  
  Call Number Admin @ si @ SVA2018 Serial 3360  
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Author Marta Ligero; Guillermo Torres; Carles Sanchez; Katerine Diaz; Raquel Perez; Debora Gil edit   pdf
url  doi
openurl 
  Title Selection of Radiomics Features based on their Reproducibility Type Conference Article
  Year 2019 Publication 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society Abbreviated Journal  
  Volume Issue Pages 403-408  
  Keywords  
  Abstract Dimensionality reduction is key to alleviate machine learning artifacts in clinical applications with Small Sample Size (SSS) unbalanced datasets. Existing methods rely on either the probabilistic distribution of training data or the discriminant power of the reduced space, disregarding the impact of repeatability and uncertainty in features.In the present study is proposed the use of reproducibility of radiomics features to select features with high inter-class correlation coefficient (ICC). The reproducibility includes the variability introduced in the image acquisition, like medical scans acquisition parameters and convolution kernels, that affects intensity-based features and tumor annotations made by physicians, that influences morphological descriptors of the lesion.For the reproducibility of radiomics features three studies were conducted on cases collected at Vall Hebron Oncology Institute (VHIO) on responders to oncology treatment. The studies focused on the variability due to the convolution kernel, image acquisition parameters, and the inter-observer lesion identification. The features selected were those features with a ICC higher than 0.7 in the three studies.The selected features based on reproducibility were evaluated for lesion malignancy classification using a different database. Results show better performance compared to several state-of-the-art methods including Principal Component Analysis (PCA), Kernel Discriminant Analysis via QR decomposition (KDAQR), LASSO, and an own built Convolutional Neural Network.  
  Address Berlin; Alemanya; July 2019  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference EMBC  
  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ LTS2019 Serial 3358  
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Author Esmitt Ramirez; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil edit   pdf
url  openurl
  Title Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy Type Conference Article
  Year 2018 Publication OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis Abbreviated Journal  
  Volume 11041 Issue Pages  
  Keywords Biopsy guiding; Bronchoscopy; Lung biopsy; Intervention guiding; Airway codification  
  Abstract Bronchoscopy examinations allow biopsy of pulmonary nodules with minimum risk for the patient. Even for experienced bronchoscopists, it is difficult to guide the bronchoscope to most distal lesions and obtain an accurate diagnosis. This paper presents an image-based codification of the bronchial anatomy for bronchoscopy biopsy guiding. The 3D anatomy of each patient is codified as a binary tree with nodes representing bronchial levels and edges labeled using their position on images projecting the 3D anatomy from a set of branching points. The paths from the root to leaves provide a codification of navigation routes with spatially consistent labels according to the anatomy observes in video bronchoscopy explorations. We evaluate our labeling approach as a guiding system in terms of the number of bronchial levels correctly codified, also in the number of labels-based instructions correctly supplied, using generalized mixed models and computer-generated data. Results obtained for three independent observers prove the consistency and reproducibility of our guiding system. We trust that our codification based on viewer’s projection might be used as a foundation for the navigation process in Virtual Bronchoscopy systems.  
  Address Granada; September 2018  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference MICCAIW  
  Notes IAM; 600.096; 600.075; 601.323; 600.145 Approved no  
  Call Number Admin @ si @ RSB2018b Serial 3137  
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