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Guillermo Torres, Debora Gil, Antoni Rosell, S. Mena, & Carles Sanchez. (2023)." Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules" In 37th International Congress and Exhibition is organized by Computer Assisted Radiology and Surgery.
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Jorge Bernal, Debora Gil, Carles Sanchez, & F. Javier Sanchez. (2014). "Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis " In 1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy (Vol. 8899, pp. 1–10). Springer International Publishing.
Abstract: In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.
Keywords: Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps
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Debora Gil, F. Javier Sanchez, Gloria Fernandez Esparrach, & Jorge Bernal. (2015). "3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos " In Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 (Vol. 9515, pp. 140–152).
Abstract: Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
Keywords: Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds
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Joel Barajas, Jaume Garcia, Francesc Carreras, Sandra Pujades, & Petia Radeva. (2005). "Angle Images Using Gabor Filters in Cardiac Tagged MRI " In Proceeding of the 2005 conference on Artificial Intelligence Research and Development (pp. 107–114). Amsterdam, The Netherlands: IOS Press.
Abstract: Tagged Magnetic Resonance Imaging (MRI) is a non-invasive technique used to examine cardiac deformation in vivo. An Angle Image is a representation of a Tagged MRI which recovers the relative position of the tissue respect to the distorted tags. Thus cardiac deformation can be estimated. This paper describes a new approach to generate Angle Images using a bank of Gabor filters in short axis cardiac Tagged MRI. Our method improves the Angle Images obtained by global techniques, like HARP, with a local frequency analysis. We propose to use the phase response of a combination of a Gabor filters bank, and use it to find a more precise deformation of the left ventricle. We demonstrate the accuracy of our method over HARP by several experimental results.
Keywords: Angle Images, Gabor Filters, Harp, Tagged Mri
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Debora Gil, Aura Hernandez-Sabate, Mireia Burnat, Steven Jansen, & Jordi Martinez-Vilalta. (2009). "Structure-Preserving Smoothing of Biomedical Images " In 13th International Conference on Computer Analysis of Images and Patterns (Vol. 5702, pp. 427–434). Springer Berlin Heidelberg.
Abstract: Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images.
Keywords: non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography.
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Petia Radeva, & Enric Marti. (1995). "An improved model of snakes for model-based segmentation " In Proceedings of Computer Analysis of Images and Patterns (pp. 515–520).
Abstract: The main advantage of segmentation by snakes consists in its ability to incorporate smoothness constraints on the detected shapes that can occur. Likewise, we propose to model snakes with other properties that reflect the information provided about the object of interest in a different extent. We consider different kinds of snakes, those searching for contours with a certain direction, those preserving an object’s model, those seeking for symmetry, those expanding open, etc. The availability of such a collection of snakes allows not only the more complete use of the knowledge about the segmented object, but also to solve some problems of the existing snakes. Our experiments on segmentation of facial features justify the usefulness of snakes with different properties.
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Aura Hernandez-Sabate, Debora Gil, David Roche, Monica M. S. Matsumoto, & Sergio S. Furuie. (2011). "Inferring the Performance of Medical Imaging Algorithms " In Pedro Real, Daniel Diaz-Pernil, Helena Molina-Abril, Ainhoa Berciano, & Walter Kropatsch (Eds.), 14th International Conference on Computer Analysis of Images and Patterns (Vol. 6854, pp. 520–528). L. Berlin: Springer-Verlag Berlin Heidelberg.
Abstract: Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence.
Keywords: Validation, Statistical Inference, Medical Imaging Algorithms.
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Hanne Kause, Patricia Marquez, Andrea Fuster, Aura Hernandez-Sabate, Luc Florack, Debora Gil, et al. (2015)." Quality Assessment of Optical Flow in Tagging MRI" In 5th Dutch Bio-Medical Engineering Conference BME2015.
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Joan M. Nuñez, Debora Gil, & Fernando Vilariño. (2013). "Finger joint characterization from X-ray images for rheymatoid arthritis assessment " In 6th International Conference on Biomedical Electronics and Devices (pp. 288–292). SciTePress.
Abstract: 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.
Keywords: Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde
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Gemma Sanchez, Josep Llados, & Enric Marti. (1997). Segmentation and analysis of linial texture in plans In Intelligence Artificielle et Complexité.. Paris.
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.
Keywords: Structural Texture, Voronoi, Hierarchical Clustering, String Matching.
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