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Author |
Debora Gil; Jaume Garcia; Aura Hernandez-Sabate; Enric Marti |
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Title |
Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy |
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Conference Article |
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Year |
2010 |
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8th Medical Imaging |
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7623 |
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762304 |
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304 |
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Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature. |
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IAM @ iam @ GGH2010a |
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1522 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Inhibition of false landmarks |
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Journal Article |
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Year |
2006 |
Publication |
Pattern Recognition Letters |
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PRL |
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Volume |
27 |
Issue |
9 |
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1022-1030 |
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Corners and junctions are landmarks characterized by the lack of differentiability in the unit tangent to the image level curve. Detectors based on differential operators are not, by their own definition, the best posed as they require a higher degree of differentiability to yield a reliable response. We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our inhibition orientation energy (IOE) landmark locator. |
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Elsevier Science Inc. |
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New York, NY, USA |
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0167-8655 |
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IAM;MILAB |
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IAM @ iam @ GiR2006 |
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1529 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Shape Restoration via a Regularized Curvature Flow |
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Journal Article |
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Year |
2004 |
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Journal of Mathematical Imaging and Vision |
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21 |
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3 |
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205-223 |
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Any image filtering operator designed for automatic shape restoration should satisfy robustness (whatever the nature and degree of noise is) as well as non-trivial smooth asymptotic behavior. Moreover, a stopping criterion should be determined by characteristics of the evolved image rather than dependent on the number of iterations. Among the several PDE based techniques, curvature flows appear to be highly reliable for strongly noisy images compared to image diffusion processes.
In the present paper, we introduce a regularized curvature flow (RCF) that admits non-trivial steady states. It is based on a measure of the local curve smoothness that takes into account regularity of the curve curvature and serves as stopping term in the mean curvature flow. We prove that this measure decreases over the orbits of RCF, which endows the method with a natural stop criterion in terms of the magnitude of this measure. Further, in its discrete version it produces steady states consisting of piece-wise regular curves. Numerical experiments made on synthetic shapes corrupted with different kinds of noise show the abilities and limitations of each of the current geometric flows and the benefits of RCF. Finally, we present results on real images that illustrate the usefulness of the present approach in practical applications. |
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IAM;MILAB |
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IAM @ iam @ GiR2004c |
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1532 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Inhibition of False Landmarks |
Type |
Book Chapter |
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Year |
2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
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233-244 |
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We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator. |
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IOS Press |
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Barcelona (Spain) |
Editor |
al, J.V. et |
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IAM;MILAB |
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IAM @ iam @ GiR2004a |
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1533 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Curvature based Distance Maps |
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Report |
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Year |
2003 |
Publication |
CVC Technical Report |
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70 |
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Computer Vision Center |
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IAM;MILAB |
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IAM @ iam @ GIR2003a |
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1534 |
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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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Conference Article |
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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; 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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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; 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 |
Publication |
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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Author |
Debora Gil; Petia Radeva; Fernando Vilariño |
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Title |
Anisotropic Contour Completion |
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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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Author |
Aura Hernandez-Sabate |
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Title |
Exploring Arterial Dynamics and Structures in IntraVascular Ultrasound Sequences |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Cardiovascular diseases are a leading cause of death in developed countries. Most of them are caused by arterial (specially coronary) diseases, mainly caused by plaque accumulation. Such pathology narrows blood flow (stenosis) and affects artery bio- mechanical elastic properties (atherosclerosis). In the last decades, IntraVascular UltraSound (IVUS) has become a usual imaging technique for the diagnosis and follow up of arterial diseases. IVUS is a catheter-based imaging technique which shows a sequence of cross sections of the artery under study. Inspection of a single image gives information about the percentage of stenosis. Meanwhile, inspection of longitudinal views provides information about artery bio-mechanical properties, which can prevent a fatal outcome of the cardiovascular disease. On one hand, dynamics of arteries (due to heart pumping among others) is a major artifact for exploring tissue bio-mechanical properties. On the other one, manual stenosis measurements require a manual tracing of vessel borders, which is a time-consuming task and might suffer from inter-observer variations. This PhD thesis proposes several image processing tools for exploring vessel dy- namics and structures. We present a physics-based model to extract, analyze and correct vessel in-plane rigid dynamics and to retrieve cardiac phase. Furthermore, we introduce a deterministic-statistical method for automatic vessel borders detection. In particular, we address adventitia layer segmentation. An accurate validation pro- tocol to ensure reliable clinical applicability of the methods is a crucial step in any proposal of an algorithm. In this thesis we take special care in designing a valida- tion protocol for each approach proposed and we contribute to the in vivo dynamics validation with a quantitative and objective score to measure the amount of motion suppressed. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Debora Gil |
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978-84-937261-6-4 |
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IAM @ iam @ Her2009 |
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1543 |
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