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Author  |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition |
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2013 |
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16th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Nagoya; Japan; September 2013 |
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MICCAI |
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Admin @ si @ VGG2013 |
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2301 |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
Optimal Medial Surface Generation for Anatomical Volume Representations |
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Book Chapter |
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2012 |
Publication |
Abdominal Imaging. Computational and Clinical Applications |
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LNCS |
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7601 |
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265-273 |
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Keywords |
Medial surface representation; volume reconstruction |
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Abstract |
Medial representations are a widely used technique in abdominal organ shape representation and parametrization. Those methods require good medial manifolds as a starting point. Any medial
surface used to parametrize a volume should be simple enough to allow an easy manipulation and complete enough to allow an accurate reconstruction of the volume. Obtaining good quality medial
surfaces is still a problem with current iterative thinning methods. This forces the usage of generic, pre-calculated medial templates that are adapted to the final shape at the cost of a drop in volume reconstruction.
This paper describes an operator for generation of medial structures that generates clean and complete manifolds well suited for their further use in medial representations of abdominal organ volumes. While being simpler than thinning surfaces, experiments show its high performance in volume reconstruction and preservation of medial surface main branching topology. |
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Nice, France |
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Springer Berlin Heidelberg |
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Yoshida, Hiroyuki and Hawkes, David and Vannier, MichaelW. |
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Lecture Notes in Computer Science |
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0302-9743 |
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978-3-642-33611-9 |
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STACOM |
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IAM @ iam @ VGG2012b |
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1988 |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
A medial map capturing the essential geometry of organs |
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Conference Article |
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2012 |
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ISBI Workshop on Open Source Medical Image Analysis software |
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1691 - 1694 |
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Medial Surface Representation, Volume Reconstruction,Geometry , Image reconstruction , Liver , Manifolds , Shape , Surface morphology , Surface reconstruction |
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Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Accurate computation of one pixel wide medial surfaces is mandatory. Those surfaces must represent faithfully the geometry of the volume. Although morphological methods produce excellent results in 2D, their complexity and quality drops across dimensions, due to a more complex description of pixel neighborhoods. This paper introduces a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Our experiments show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume |
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Barcelona,Spain |
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IEEE |
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1945-7928 |
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978-1-4577-1857-1 |
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ISBI |
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IAM @ iam @ VGG2012a |
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1989 |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
A Novel Cochlear Reference Frame Based On The Laplace Equation |
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Conference Article |
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2015 |
Publication |
29th international Congress and Exhibition on Computer Assisted Radiology and Surgery |
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10 |
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1 |
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1-312 |
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Poster |
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Barcelona; Spain; June 2015 |
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CARS |
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IAM; 600.075 |
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Admin @ si @ VGG2015 |
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2615 |
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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 |
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Biopsia virtual radiomica para el diagnóstico histológico de nódulos pulmonares – Resultados intermedios del proyecto Radiolung |
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Conference Article |
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2023 |
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SEPAR |
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Granada; Spain; June 2023 |
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Admin @ si @ BGS2023 |
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3951 |
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Sonia Baeza; Debora Gil; I.Garcia Olive; M.Salcedo; J.Deportos; Carles Sanchez; Guillermo Torres; G.Moragas; Antoni Rosell |
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Title |
A novel intelligent radiomic analysis of perfusion SPECT/CT images to optimize pulmonary embolism diagnosis in COVID-19 patients |
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Journal Article |
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2022 |
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EJNMMI Physics |
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EJNMMI-PHYS |
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9 |
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1, Article 84 |
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1-17 |
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Background: COVID-19 infection, especially in cases with pneumonia, is associated with a high rate of pulmonary embolism (PE). In patients with contraindications for CT pulmonary angiography (CTPA) or non-diagnostic CTPA, perfusion single-photon emission computed tomography/computed tomography (Q-SPECT/CT) is a diagnostic alternative. The goal of this study is to develop a radiomic diagnostic system to detect PE based only on the analysis of Q-SPECT/CT scans.
Methods: This radiomic diagnostic system is based on a local analysis of Q-SPECT/CT volumes that includes both CT and Q-SPECT values for each volume point. We present a combined approach that uses radiomic features extracted from each scan as input into a fully connected classifcation neural network that optimizes a weighted crossentropy loss trained to discriminate between three diferent types of image patterns (pixel sample level): healthy lungs (control group), PE and pneumonia. Four types of models using diferent confguration of parameters were tested.
Results: The proposed radiomic diagnostic system was trained on 20 patients (4,927 sets of samples of three types of image patterns) and validated in a group of 39 patients (4,410 sets of samples of three types of image patterns). In the training group, COVID-19 infection corresponded to 45% of the cases and 51.28% in the test group. In the test group, the best model for determining diferent types of image patterns with PE presented a sensitivity, specifcity, positive predictive value and negative predictive value of 75.1%, 98.2%, 88.9% and 95.4%, respectively. The best model for detecting
pneumonia presented a sensitivity, specifcity, positive predictive value and negative predictive value of 94.1%, 93.6%, 85.2% and 97.6%, respectively. The area under the curve (AUC) was 0.92 for PE and 0.91 for pneumonia. When the results obtained at the pixel sample level are aggregated into regions of interest, the sensitivity of the PE increases to 85%, and all metrics improve for pneumonia.
Conclusion: This radiomic diagnostic system was able to identify the diferent lung imaging patterns and is a frst step toward a comprehensive intelligent radiomic system to optimize the diagnosis of PE by Q-SPECT/CT. |
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5 dec 2022 |
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Springer |
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Admin @ si @ BGG2022 |
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3759 |
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Author |
Sonia Baeza; R.Domingo; M.Salcedo; G.Moragas; J.Deportos; I.Garcia Olive; Carles Sanchez; Debora Gil; Antoni Rosell |
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Title |
Artificial Intelligence to Optimize Pulmonary Embolism Diagnosis During Covid-19 Pandemic by Perfusion SPECT/CT, a Pilot Study |
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2021 |
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American Journal of Respiratory and Critical Care Medicine |
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IAM; 600.145 |
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Admin @ si @ BDS2021 |
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3591 |
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