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Author Guillermo Torres; Jan Rodríguez Dueñas; Sonia Baeza; Antoni Rosell; Carles Sanchez; Debora Gil edit   pdf
url  openurl
  Title Prediction of Malignancy in Lung Cancer using several strategies for the fusion of Multi-Channel Pyradiomics Images Type Conference Article
  Year 2023 Publication 7th Workshop on Digital Image Processing for Medical and Automotive Industry in the framework of SYNASC 2023 Abbreviated Journal  
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  Abstract This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level.  
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  Area Expedition Conference DIPMAI  
  Notes IAM Approved no  
  Call Number Admin @ si @ TRB2023 Serial 3926  
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Author Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez edit  openurl
  Title Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules Type Conference Article
  Year 2023 Publication 37th International Congress and Exhibition is organized by Computer Assisted Radiology and Surgery Abbreviated Journal  
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  Address Munich; Germany; June 2023  
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  Area Expedition Conference CARS  
  Notes IAM Approved no  
  Call Number Admin @ si @ TGR2023a Serial 3950  
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Author 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 edit  openurl
  Title Biopsia virtual radiomica para el diagnóstico histológico de nódulos pulmonares – Resultados intermedios del proyecto Radiolung Type Conference Article
  Year 2023 Publication SEPAR Abbreviated Journal  
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  Address Granada; Spain; June 2023  
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  ISSN ISBN Medium  
  Area Expedition Conference SEPAR  
  Notes IAM Approved no  
  Call Number Admin @ si @ BGS2023 Serial 3951  
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Author Debora Gil; Guillermo Torres; Carles Sanchez edit  openurl
  Title Transforming radiomic features into radiological words Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
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  Address Cartagena de Indias; Colombia; April 2023  
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  ISSN ISBN Medium  
  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ GTS2023 Serial 3952  
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Author Pau Cano; Debora Gil; Eva Musulen edit  openurl
  Title Towards automatic detection of helicobacter pylori in histological samples of gastric tissue Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
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  Address Cartagena de Indias; Colombia; April 2023  
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  ISSN ISBN Medium  
  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ CGM2023 Serial 3953  
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Author Guillermo Torres; Debora Gil; Antonio Rosell; Sonia Baeza; Carles Sanchez edit  openurl
  Title A radiomic biopsy for virtual histology of pulmonary nodules Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
  Volume Issue (up) Pages  
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  Abstract Pòster  
  Address Cartagena de Indias; Colombia; April 2023  
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  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ TGR2023b Serial 3954  
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Author Jose Elias Yauri edit  openurl
  Title Deep Learning Based Data Fusion Approaches for the Assessment of Cognitive States on EEG Signals Type Book Whole
  Year 2023 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
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  Abstract For millennia, the study of the couple brain-mind has fascinated the humanity in order to understand the complex nature of cognitive states. A cognitive state is the state of the mind at a specific time and involves cognition activities to acquire and process information for making a decision, solving a problem, or achieving a goal.
While normal cognitive states assist in the successful accomplishment of tasks; on the contrary, abnormal states of the mind can lead to task failures due to a reduced cognition capability. In this thesis, we focus on the assessment of cognitive states by means of the analysis of ElectroEncephaloGrams (EEG) signals using deep learning methods. EEG records the electrical activity of the brain using a set of electrodes placed on the scalp that output a set of spatiotemporal signals that are expected to be correlated to a specific mental process.
From the point of view of artificial intelligence, any method for the assessment of cognitive states using EEG signals as input should face several challenges. On the one hand, one should determine which is the most suitable approach for the optimal combination of the multiple signals recorded by EEG electrodes. On the other hand, one should have a protocol for the collection of good quality unambiguous annotated data, and an experimental design for the assessment of the generalization and transfer of models. In order to tackle them, first, we propose several convolutional neural architectures to perform data fusion of the signals recorded by EEG electrodes, at raw signal and feature levels. Four channel fusion methods, easy to incorporate into any neural network architecture, are proposed and assessed. Second, we present a method to create an unambiguous dataset for the prediction of cognitive mental workload using serious games and an Airbus-320 flight simulator. Third, we present a validation protocol that takes into account the levels of generalization of models based on the source and amount of test data.
Finally, the approaches for the assessment of cognitive states are applied to two use cases of high social impact: the assessment of mental workload for personalized support systems in the cockpit and the detection of epileptic seizures. The results obtained from the first use case show the feasibility of task transfer of models trained to detect workload in serious games to real flight scenarios. The results from the second use case show the generalization capability of our EEG channel fusion methods at k-fold cross-validation, patient-specific, and population levels.
 
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher IMPRIMA Place of Publication Editor Aura Hernandez;Debora Gil  
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  Notes IAM Approved no  
  Call Number Admin @ si @ Yau2023 Serial 3962  
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Author Debora Gil; Petia Radeva edit   pdf
doi  openurl
  Title Extending anisotropic operators to recover smooth shapes Type Journal Article
  Year 2005 Publication Computer Vision and Image Understanding Abbreviated Journal  
  Volume 99 Issue (up) 1 Pages 110-125  
  Keywords Contour completion; Functional extension; Differential operators; Riemmanian manifolds; Snake segmentation  
  Abstract Anisotropic differential operators are widely used in image enhancement processes. Recently, their property of smoothly extending functions to the whole image domain has begun to be exploited. Strong ellipticity of differential operators is a requirement that ensures existence of a unique solution. This condition is too restrictive for operators designed to extend image level sets: their own functionality implies that they should restrict to some vector field. The diffusion tensor that defines the diffusion operator links anisotropic processes with Riemmanian manifolds. In this context, degeneracy implies restricting diffusion to the varieties generated by the vector fields of positive eigenvalues, provided that an integrability condition is satisfied. We will use that any smooth vector field fulfills this integrability requirement to design line connection algorithms for contour completion. As application we present a segmenting strategy that assures convergent snakes whatever the geometry of the object to be modelled is.  
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  Series Volume Series Issue Edition  
  ISSN 1077-3142 ISBN Medium  
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  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GIR2005 Serial 1530  
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Author Aura Hernandez-Sabate; Debora Gil; Jaume Garcia; Enric Marti edit   pdf
doi  openurl
  Title Image-based Cardiac Phase Retrieval in Intravascular Ultrasound Sequences Type Journal Article
  Year 2011 Publication IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control Abbreviated Journal T-UFFC  
  Volume 58 Issue (up) 1 Pages 60-72  
  Keywords 3-D exploring; ECG; band-pass filter; cardiac motion; cardiac phase retrieval; coronary arteries; electrocardiogram signal; image intensity local mean evolution; image-based cardiac phase retrieval; in vivo pullbacks acquisition; intravascular ultrasound sequences; longitudinal motion; signal extrema; time 36 ms; band-pass filters; biomedical ultrasonics; cardiovascular system; electrocardiography; image motion analysis; image retrieval; image sequences; medical image processing; ultrasonic imaging  
  Abstract Longitudinal motion during in vivo pullbacks acquisition of intravascular ultrasound (IVUS) sequences is a major artifact for 3-D exploring of coronary arteries. Most current techniques are based on the electrocardiogram (ECG) signal to obtain a gated pullback without longitudinal motion by using specific hardware or the ECG signal itself. We present an image-based approach for cardiac phase retrieval from coronary IVUS sequences without an ECG signal. A signal reflecting cardiac motion is computed by exploring the image intensity local mean evolution. The signal is filtered by a band-pass filter centered at the main cardiac frequency. Phase is retrieved by computing signal extrema. The average frame processing time using our setup is 36 ms. Comparison to manually sampled sequences encourages a deeper study comparing them to ECG signals.  
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  Series Volume Series Issue Edition  
  ISSN 0885-3010 ISBN Medium  
  Area Expedition Conference  
  Notes IAM;ADAS Approved no  
  Call Number IAM @ iam @ HGG2011 Serial 1546  
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Author Enric Marti; Debora Gil; Carme Julia edit   pdf
openurl 
  Title A PBL experience in the teaching of Computer Graphics Type Conference Article
  Year 2005 Publication EUROGRAPHICS Proceedings Abbreviated Journal  
  Volume 5 Issue (up) 1 Pages 95-103  
  Keywords project-based learning; computer graphics education; Open GL; rendering techniques; computer animation techniques; Graphics packages; Hierarchy and geometric transformations; Animation; Color; shading; shadowing and texture; fractals; hidden line/surface removal; Problem Based Learning  
  Abstract Project-Based Learning (PBL) is an educational strategy to improve student’s learning capability that, in recent years, has had a progressive acceptance in undergraduate studies. This methodology is based on solving a problem or project in a student working group. In this way, PBL focuses on learning the necessary tools to correctly find a solution to given problems. Since the learning initiative is transferred to the student, the PBL method promotes students own abilities. This allows a better assessment of the true workload that carries out the student in the subject. It follows that the methodology conforms to the guidelines of the Bologna document, which quantifies the student workload in a subject by means of the European credit transfer system (ECTS). PBL is currently applied in undergraduate studies needing strong practical training such as medicine, nursing or law sciences. Although this is also the case in engineering studies, amazingly, few experiences have been reported. In this paper we propose to use PBL in the educational organization of the Computer Graphics subjects in the Computer Science degree. Our PBL project focuses in the development of a C++ graphical environment based on the OpenGL libraries for visualization and handling of different graphical objects. The starting point is a basic skeleton that already includes lighting functions, perspective projection with mouse interaction to change the point of view and three predefined objects. Students have to complete this skeleton by adding their own functions to solve the project. A total number of 10 projects have been proposed and successfully solved. The exercises range from human face rendering to articulated objects, such as robot arms or puppets. In the present paper we extensively report the statement and educational objectives for two of the projects: solar system visualization and a chess game. We report our earlier educational experience based on the standard classroom theoretical, problem and practice sessions and the reasons that motivated searching for other learning methods. We have mainly chosen PBL because it improves the student learning initiative. We have applied the PBL educational model since the beginning of the second semester. The student’s feedback increases in his interest for the subject. We present a comparative study of the teachers’ and students’ workload between PBL and the classic teaching approach, which suggests that the workload increase in PBL is not as high as it seems.  
  Address Dublin; Ireland; September 2005  
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  Area Expedition Conference EUROGRAPHICS  
  Notes IAM;ADAS; Approved no  
  Call Number IAM @ iam @ MGJ2005 Serial 1593  
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