|
|
Hanne Kause, Aura Hernandez-Sabate, Patricia Marquez, Andrea Fuster, Luc Florack, Hans van Assen, et al. (2015). "Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging " In Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 (Vol. 9534, pp. 69–79). Springer International Publishing.
Abstract: Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm.
|
|
|
|
Jaume Garcia. (2009). "Statistical Models of the Architecture and Function of the Left Ventricle " (Debora Gil, Ed.). Ph.D. thesis, Ediciones Graficas Rey, .
Abstract: Cardiovascular Diseases, specially those affecting the Left Ventricle (LV), are the leading cause of death in developed countries with approximately a 30% of all global deaths. In order to address this public health concern, physicians focus on diagnosis and therapy planning. On one hand, early and accurate detection of Regional Wall Motion Abnormalities (RWMA) significantly contributes to a quick diagnosis and prevents the patient to reach more severe stages. On the other hand, a thouroughly knowledge of the normal gross anatomy of the LV, as well as, the distribution of its muscular fibers is crucial for designing specific interventions and therapies (such as pacemaker implanction). Statistical models obtained from the analysis of different imaging modalities allow the computation of the normal ranges of variation within a given population. Normality models are a valuable tool for the definition of objective criterions quantifying the degree of (anomalous) deviation of the LV function and anatomy for a given subject. The creation of statistical models involve addressing three main issues: extraction of data from images, definition of a common domain for comparison of data across patients and designing appropriate statistical analysis schemes. In this PhD thesis we present generic image processing tools for the creation of statistical models of the LV anatomy and function. On one hand, we use differential geometry concepts to define a computational framework (the Normalized Parametric Domain, NPD) suitable for the comparison and fusion of several clinical scores obtained over the LV. On the other hand, we present a variational approach (the Harmonic Phase Flow, HPF) for the estimation of myocardial motion that provides dense and continuous vector fields without overestimating motion at injured areas. These tools are used for the creation of statistical models. Regarding anatomy, we obtain an atlas jointly modelling, both, LV gross anatomy and fiber architecture. Regarding function, we compute normality patterns of scores characterizing the (global and local) LV function and explore, for the first time, the configuration of local scores better suited for RWMA detection.
|
|
|
|
Jaume Garcia, Debora Gil, & Aura Hernandez-Sabate. (2010). "Endowing Canonical Geometries to Cardiac Structures " In O. Camara, M. Pop, K. Rhode, M. Sermesant, N. Smith, & A. Young (Eds.), Statistical Atlases And Computational Models Of The Heart (Vol. 6364, pp. 124–133). Lecture Notes in Computer Science. Springer Berlin / Heidelberg.
Abstract: International conference on Cardiac electrophysiological simulation challenge
In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view.
|
|
|
|
Jaume Garcia, Petia Radeva, & Francesc Carreras. (2004). "Combining Spectral and Active Shape methods to Track Tagged MRI " In Recent Advances in Artificial Intelligence Research and Development (pp. 37–44). IOS Press.
Abstract: Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising.
Keywords: MR; tagged MR; ASM; LV segmentation; motion estimation.
|
|
|
|
Jose Elias Yauri. (2023)." Deep Learning Based Data Fusion Approaches for the Assessment of Cognitive States on EEG Signals" (Aura Hernandez, & Debora Gil, Eds.). Ph.D. thesis, IMPRIMA, .
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.
|
|
|
|
Josep Llados, Ernest Valveny, Gemma Sanchez, & Enric Marti. (2002). "Symbol recognition: current advances and perspectives " In Dorothea Blostein and Young- Bin Kwon (Ed.), Graphics Recognition Algorithms And Applications (Vol. 2390, pp. 104–128). Lecture Notes in Computer Science. Springer-Verlag.
Abstract: The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
|
|
|
|
Josep Llados, Gemma Sanchez, & Enric Marti. (1998). "A string based method to recognize symbols and structural textures in architectural plans " In Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers (Vol. 1389, pp. 91–103). LNCS. Springer Link.
Abstract: This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
|
|
|
|
Josep Llados, Jaime Lopez-Krahe, & Enric Marti. (1997). "A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform " In Machine Vision and Applications (Vol. 10, pp. 150–158).
Abstract: Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input.
Keywords: Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition
|
|
|
|
Misael Rosales, Petia Radeva, Oriol Rodriguez, & Debora Gil. (2005). "Suppression of IVUS Image Rotation. A Kinematic Approach " In Monica Andres and Hernandez Petia and Santos A. and R. Frangi (Ed.), Functional Imaging and Modeling of the Heart (Vol. 3504, pp. 889–892). Lecture Notes in Computer Science, 3504. Springer Berlin / Heidelberg.
Abstract: IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.
|
|
|
|
Ole Vilhelm-Larsen, Petia Radeva, & Enric Marti. (1995). "Guidelines for choosing optimal parameters of elasticity for snakes " In Computer Analysis Of Images And Patterns (Vol. 970, pp. 106–113). Lecture Notes in Computer Science.
Abstract: This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.
|
|
