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Debora Gil; Aura Hernandez-Sabate; Mireia Burnat; Steven Jansen; Jordi Martinez-Vilalta |
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Title |
Structure-Preserving Smoothing of Biomedical Images |
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Conference Article |
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2009 |
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13th International Conference on Computer Analysis of Images and Patterns |
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5702 |
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427-434 |
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non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography. |
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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. |
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Münster, Germany |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-03766-5 |
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CAIP |
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IAM |
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IAM @ iam @ GHB2009 |
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1527 |
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Author |
M.Gomez; Josefina Mauri; Eduard Fernandez-Nofrerias; Oriol Rodriguez-Leon; Carme Julia; Debora Gil; Petia Radeva |
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Title |
Reconstrucción de un modelo espacio-temporal de la luz del vaso a partir de secuencias de ecografía intracoronaria |
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Conference Article |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. |
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IAM;ADAS;MILAB |
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IAM @ iam @ GMF2002d |
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1516 |
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Author |
Jaume Garcia; David Rotger; Francesc Carreras; R.Leta; Petia Radeva |
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Title |
Contrast echography segmentation and tracking by trained deformable models |
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Conference Article |
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Year |
2003 |
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Proc. Computers in Cardiology |
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30 |
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173-176 |
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The objective of this work is to segment the human left ventricle myocardium (LVM) in contrast echocardiography imaging and thus track it along a cardiac cycle in order to extract quantitative data about heart function. Ultrasound images are hard to work with due to their speckle appearance. To overcome this we report the combination of active contour models (ACM) or snakes and active shape models (ASM). The ability of ACM in giving closed and smooth curves in addition to the power of the ASM in producing shapes similar to the ones learned, evoke to a robust algorithm. Meanwhile the snake is attracted towards image main features, ASM acts as a correction factor. The algorithm was tested independently on 180 frames and satisfying results were obtained: in 95% the maximum difference between automatic and experts segmentation was less than 12 pixels. |
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Centre de Visió per Computador – Dept. Informàtica, UAB Edifici O – Campus UAB, 08193 Bellater |
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0276-6547 |
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0-7803-8170-X |
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IAM;MILAB |
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IAM @ iam @ GRC2003 |
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1512 |
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Author |
Debora Gil; Petia Radeva; Josefina Mauri |
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Title |
Ivus Segmentation Via a Regularized Curvature Flow |
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Year |
2002 |
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X Congreso Anual de la Sociedad Española de Ingeniería Biomédica CASEIB 2002 |
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133-136 |
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Cardiac diseases are diagnosed and treated through a study of the morphology and dynamics of cardiac arteries. In- travascular Ultrasound (IVUS) imaging is of high interest to physicians since it provides both information. At the current state-of-the-art in image segmentation, a robust detection of the arterial lumen in IVUS demands manual intervention or ECG-gating. Manual intervention is a tedious and time consuming task that requires experienced observers, meanwhile ECG-gating is an acquisition technique not available in all clinical centers. We introduce a parametric algorithm that detects the arterial luminal border in in vivo sequences. The method consist in smoothing the sequences’ level surfaces under a regularized mean curvature flow that admits non-trivial steady states. The flow is based on a measure of the surface local smoothness that takes into account regularity of the surface curvature. |
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Saragossa, Espanya |
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IAM;MILAB |
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IAM @ iam @ GRM2002 |
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1536 |
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Author |
Debora Gil; Oriol Rodriguez; Josepa Mauri; Petia Radeva |
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Title |
Statistical descriptors of the Myocardial perfusion in angiographic images |
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Conference Article |
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Year |
2006 |
Publication |
Proc. Computers in Cardiology |
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677-680 |
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Anisotropic processing; intravascular ultrasound (IVUS); vessel border segmentation; vessel structure classification. |
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Restoration of coronary flow after primary percutaneous coronary intervention in acute myocardial infarction does not always correlate with adequate myocardial perfusion. Recently, coronary angiography has been used to assess microcirculation integrity (Myocardial BlushAnalysis, MBA). Although MBA correlates with patient prognosis there are few image processing methods addressing objective perfusion quantification. The goal of this work is to develop statistical descriptors of the myocardial dyeing pattern allowing objective assessment of myocardial perfusion. Experiments on healthy right coronary arteries show that our approach allows reliable measurements without any specific image acquisition protocol. |
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IAM;MILAB |
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IAM @ iam @ GRR2006 |
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1528 |
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Author |
Debora Gil; Petia Radeva; Jordi Saludes; Josefina Mauri |
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Title |
Automatic Segmentation of Artery Wall in Coronary IVUS Images: a Probabilistic Approach |
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Conference Article |
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2000 |
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Proceedings of CIC’2000 |
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Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results. |
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Cambridge, Massachussets |
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CIC |
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IAM;MILAB |
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IAM @ iam @ GRS2000 |
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1538 |
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Debora Gil; Petia Radeva; Jordi Saludes; Josefina Mauri |
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Automatic Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach |
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2000 |
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International Conference on Pattern Recognition |
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4 |
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352-355 |
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Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results. |
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IAM;MILAB |
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IAM @ iam @ GRS2000a |
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1537 |
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Author |
Debora Gil; Petia Radeva; Fernando Vilariño |
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Title |
Anisotropic Contour Completion |
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Conference Article |
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2003 |
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Proceedings of the IEEE International Conference on Image Processing |
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In this paper we introduce a novel application of the diffusion tensor for anisotropic image processing. The Anisotropic Contour Completion (ACC) we suggest consists in extending the characteristic function of the open curve by means of a degenerated diffusion tensor that prevents any diffusion in the normal direction. We show that ACC is equivalent to a dilation with a continuous elliptic structural element that takes into account the local orientation of the contours to be closed. Experiments on contours extracted from real images show that ACC produces shapes able to adapt to any curve in an active contour framework. 1. |
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Barcelona, Spain |
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0-7803-7751-6 |
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IAM;MV;MILAB;SIAI |
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IAM @ iam @ GRV2003 |
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1539 |
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Aura Hernandez-Sabate; Debora Gil; Josefina Mauri; Petia Radeva |
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Title |
Reducing cardiac motion in IVUS sequences |
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Conference Article |
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2006 |
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Proceeding of Computers in Cardiology |
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33 |
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685-688 |
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Cardiac vessel displacement is a main artifact in IVUS sequences. It hinders visualization of the main structures in an appropriate orientation and alignment and affects extracting vessel measurements. In this paper, we present a novel approach for image sequence alignment based on spectral analysis, which removes rigid dynamics, preserving at the same time the vessel geometry. First, we suppress the translation by taking, for each frame, the center of mass of the image as origin of coordinates. In polar coordinates with such point as origin, the rotation appears as a horizontal displacement. The translation induces a phase shift in the Fourier coefficients of two consecutive polar images. We estimate the phase by adjusting a regression plane to the phases of the principal frequencies. Experiments show that the presented strategy suppress cardiac motion regardless of the acquisition device. 1. |
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IAM; MILAB |
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IAM @ iam @ HGM2006a |
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1554 |
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Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias |
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Title |
Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images |
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Conference Article |
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2004 |
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Proc. Computers in Cardiology |
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31 |
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229-232 |
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The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles |
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Chicago (USA) |
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IAM; MILAB |
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IAM @ iam @ HGR2004 |
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1555 |
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