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Pablo Lamata
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2020 – today
- 2024
- [j28]Uxio Hermida
, Milou P. M. van Poppel
The onset of coarctation of the aorta before birth: Mechanistic insights from fetal arch anatomy and haemodynamics. Comput. Biol. Medicine 182: 109077 (2024) - [i9]David Stojanovski, Mariana da Silva, Pablo Lamata, Arian Beqiri, Alberto Gómez:
Efficient Semantic Diffusion Architectures for Model Training on Synthetic Echocardiograms. CoRR abs/2409.19371 (2024) - 2023
- [c36]Malak Sabry, Pablo Lamata, Andreas Sigfridsson, Hamed Keramati, Alexander Fyrdahl
Vortex Duration Time to Infer Pulmonary Hypertension: In-Silico Emulation and Dependence on Quantification Technique. FIMH 2023: 425-434 - [c35]Uxio Hermida
Shape-Guided In-Silico Characterization of 3D Fetal Arch Hemodynamics in Suspected Coarctation of the Aorta. FIMH 2023: 495-504 - [c34]Debbie Zhao, João Filipe Fernandes, Stephen A. Creamer
Left Ventricular Work and Power are Constant Despite Varying Cardiac Cycle Length - Implications for Patients with Atrial Fibrillation. FIMH 2023: 708-717 - [c33]David Stojanovski
Echo from Noise: Synthetic Ultrasound Image Generation Using Diffusion Models for Real Image Segmentation. ASMUS@MICCAI 2023: 34-43 - [c32]Paula Ramirez Gilliland
Towards Automatic Risk Prediction of Coarctation of the Aorta from Fetal CMR Using Atlas-Based Segmentation and Statistical Shape Modelling. PIPPI@MICCAI 2023: 53-63 - [c31]Malak Sabry, Uxio Hermida, Ahmed Hassan, Michael Nagy, David Stojanovski, Irini Samuel, John Locas, Magdi H. Yacoub, Adelaide de Vecchi, Pablo Lamata:
Exploring the Relationship Between Pulmonary Artery Shape and Pressure in Pulmonary Hypertension: A Statistical Shape Analysis Study. STACOM@MICCAI 2023: 186-195 - [p1]Alistair A. Young, Steffen E. Petersen, Pablo Lamata:
AI in the Real World. AI and Big Data in Cardiology 2023: 171-182 - [i8]David Stojanovski, Uxio Hermida, Pablo Lamata, Arian Beqiri, Alberto Gómez:
Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentation. CoRR abs/2305.05424 (2023) - 2022
- [j27]Cristóbal Rodero
Impact of anatomical reverse remodelling in the design of optimal quadripolar pacing leads: A computational study. Comput. Biol. Medicine 140: 105073 (2022) - [j26]Cristóbal Rodero, Marina Strocchi, Maciej Marciniak, Stefano Longobardi, John Whitaker, Mark D. O'Neill, Karli Gillette, Christoph M. Augustin, Gernot Plank, Edward J. Vigmond, Pablo Lamata, Steven A. Niederer:
Correction: Linking statistical shape models and simulated function in the healthy adult human heart. PLoS Comput. Biol. 18(5) (2022) - [c30]Antonia A. Pontiki, Sara De Angelis, Connor Dibblin, Isabella Trujillo-Cortes, Pablo Lamata, Richard James Housden, Giulia Benedetti
Development and Evaluation of a Rib Statistical Shape Model for Thoracic Surgery. EMBC 2022: 3758-3763 - [c29]David Stojanovski
Efficient Pix2Vox++ for 3D Cardiac Reconstruction from 2D Echo Views. ASMUS@MICCAI 2022: 86-95 - [c28]Marcel Beetz, Jorge Corral Acero, Abhirup Banerjee
Mesh U-Nets for 3D Cardiac Deformation Modeling. STACOM@MICCAI 2022: 245-257 - [c27]Uxio Hermida
Simplifying Disease Staging Models into a Single Anatomical Axis - A Case Study of Aortic Coarctation In-utero. STACOM@MICCAI 2022: 269-279 - [c26]Marcel Beetz, Jorge Corral Acero, Abhirup Banerjee
Post-Infarction Risk Prediction with Mesh Classification Networks. STACOM@MICCAI 2022: 291-301 - [i7]David Stojanovski, Uxio Hermida
Efficient Pix2Vox++ for 3D Cardiac Reconstruction from 2D echo views. CoRR abs/2207.13424 (2022) - 2021
- [j25]David Marlevi, Maximilian Balmus, Andreas Hessenthaler
Non-invasive estimation of relative pressure for intracardiac flows using virtual work-energy. Medical Image Anal. 68: 101948 (2021) - [j24]Cristóbal Rodero
Linking statistical shape models and simulated function in the healthy adult human heart. PLoS Comput. Biol. 17(4) (2021) - [j23]Andrew Gilbert
Generating Synthetic Labeled Data From Existing Anatomical Models: An Example With Echocardiography Segmentation. IEEE Trans. Medical Imaging 40(10): 2783-2794 (2021) - 2020
- [j22]David Marlevi
Non-invasive estimation of relative pressure in turbulent flow using virtual work-energy. Medical Image Anal. 60 (2020) - [j21]Nicoló Savioli, Enrico Grisan
Real-time diameter of the fetal aorta from ultrasound. Neural Comput. Appl. 32(11): 6735-6744 (2020) - [i6]Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas K. Maier, Xin Yang, Pheng-Ann Heng, Dong Ni, Caizi Li, Qianqian Tong, Weixin Si, Élodie Puybareau, Younes Khoudli, Thierry Géraud, Chen Chen, Wenjia Bai, Daniel Rueckert, Lingchao Xu, Xiahai Zhuang, Xinzhe Luo, Shuman Jia, Maxime Sermesant, Yashu Liu, Kuanquan Wang, Davide Borra
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging. CoRR abs/2004.12314 (2020)
2010 – 2019
- 2019
- [j20]Gabriel Balaban
Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort. PLoS Comput. Biol. 15(10) (2019) - [c25]Anastasia Nasopoulou, David A. Nordsletten
Solution to the Unknown Boundary Tractions in Myocardial Material Parameter Estimations. FIMH 2019: 313-322 - [c24]Jorge Corral Acero
SMOD - Data Augmentation Based on Statistical Models of Deformation to Enhance Segmentation in 2D Cine Cardiac MRI. FIMH 2019: 361-369 - [c23]Shu Wang, Harminder Gill, Weifeng Wan, Helen Tricker, João Filipe Fernandes, Yohan Noh
Manufacturing of Ultrasound- and MRI-Compatible Aortic Valves Using 3D Printing for Analysis and Simulation. STACOM@MICCAI 2019: 12-21 - [c22]Eric Kerfoot
Synthesising Images and Labels Between MR Sequence Types with CycleGAN. DART/MIL3ID@MICCAI 2019: 45-53 - [c21]Jorge Corral Acero
Left Ventricle Quantification with Cardiac MRI: Deep Learning Meets Statistical Models of Deformation. STACOM@MICCAI 2019: 384-394 - 2018
- [c20]Nicoló Savioli, Silvia Visentin, Erich Cosmi, Enrico Grisan
Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound. ICANN (2) 2018: 148-157 - [c19]Nicoló Savioli, Giovanni Montana, Pablo Lamata:
V-FCNN: Volumetric Fully Convolution Neural Network for Automatic Atrial Segmentation. STACOM@MICCAI 2018: 273-281 - [c18]Nicoló Savioli, Miguel Silva Vieira, Pablo Lamata, Giovanni Montana:
Automated Segmentation on the Entire Cardiac Cycle Using a Deep Learning Work - Flow. SNAMS 2018: 153-158 - [i5]Nicoló Savioli, Silvia Visentin, Erich Cosmi, Enrico Grisan, Pablo Lamata, Giovanni Montana:
Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound. CoRR abs/1807.04056 (2018) - [i4]Nicoló Savioli, Giovanni Montana, Pablo Lamata:
V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation. CoRR abs/1808.01944 (2018) - [i3]Nicoló Savioli, Miguel S. Vieira
Automated segmentation on the entire cardiac cycle using a deep learning work-flow. CoRR abs/1809.01015 (2018) - [i2]Nicoló Savioli, Miguel Silva Vieira
A Generative Adversarial Model for Right Ventricle Segmentation. CoRR abs/1810.03969 (2018) - 2017
- [c17]Anastasia Nasopoulou, David A. Nordsletten
Feasibility of the Estimation of Myocardial Stiffness with Reduced 2D Deformation Data. FIMH 2017: 357-368 - 2016
- [j19]Spiros Koulouzis
Distributed Data Management Service for VPH Applications. IEEE Internet Comput. 20(2): 34-41 (2016) - [c16]Angela W. C. Lee, Manav Sohal, Jonathan M. Behar, Simon Claridge, Anoop Shetty, Thomas Jackson, Eoin R. Hyde, Gernot Plank, Reza Razavi, Pablo Lamata, Christopher Aldo Rinaldi, Steven A. Niederer:
Personalised Biophysical Model to Optimise Left Ventricle Pacing Location for Cardiac Resynchronisation Therapy Over Time. CinC 2016 - [c15]Rudra P. K. Poudel, Pablo Lamata
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation. RAMBO+HVSMR@MICCAI 2016: 83-94 - [i1]Rudra P. K. Poudel, Pablo Lamata, Giovanni Montana:
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation. CoRR abs/1608.03974 (2016) - 2015
- [j18]Fabrizio Donati
Non-invasive pressure difference estimation from PC-MRI using the work-energy equation. Medical Image Anal. 26(1): 159-172 (2015) - [j17]Sander Land
Improving the Stability of Cardiac Mechanical Simulations. IEEE Trans. Biomed. Eng. 62(3): 939-947 (2015) - [c14]Ernesto Zacur
Revealing Differences in Anatomical Remodelling of the Systemic Right Ventricle. FIMH 2015: 99-107 - [c13]Anastasia Nasopoulou, Bojan Blazevic, Andrew Crozier, Wenzhe Shi, Anoop Shetty, C. Aldo Rinaldi
Myocardial Stiffness Estimation: A Novel Cost Function for Unique Parameter Identification. FIMH 2015: 355-363 - [c12]Jack Allen
Myocardial Infarction Detection from Left Ventricular Shapes Using a Random Forest. STACOM@MICCAI 2015: 180-189 - 2014
- [j16]Matthew McCormick, David Nordsletten
Computational analysis of the importance of flow synchrony for cardiac ventricular assist devices. Comput. Biol. Medicine 49: 83-94 (2014) - [j15]Øyvind Nordbø, Pablo Lamata
A computational pipeline for quantification of mouse myocardial stiffness parameters. Comput. Biol. Medicine 53: 65-75 (2014) - [j14]Adelaide de Vecchi
Catheter-Induced Errors in Pressure Measurements in Vessels: An In-Vitro and Numerical Study. IEEE Trans. Biomed. Eng. 61(6): 1844-1850 (2014) - [c11]Fabrizio Donati, David A. Nordsletten
Pressure mapping from flow imaging: Enhancing computation of the viscous term through velocity reconstruction in near-wall regions. EMBC 2014: 5097-5100 - [c10]Sander Land
Estimation of Diastolic Biomarkers: Sensitiviy to Fibre Orientation. STACOM 2014: 105-113 - 2013
- [j13]Eric Kerfoot
Share and enjoy: anatomical models database - generating and sharing cardiovascular model data using web services. Medical Biol. Eng. Comput. 51(11): 1181-1190 (2013) - [j12]Catalina Tobon-Gomez, Nicolas Duchateau
Understanding the mechanisms amenable to CRT response: from pre-operative multimodal image data to patient-specific computational models. Medical Biol. Eng. Comput. 51(11): 1235-1250 (2013) - [j11]Jiahe Xi, Pablo Lamata
The estimation of patient-specific cardiac diastolic functions from clinical measurements. Medical Image Anal. 17(2): 133-146 (2013) - [j10]Ayush Goyal, Jack Lee, Pablo Lamata
Model-Based Vasculature Extraction From Optical Fluorescence Cryomicrotome Images. IEEE Trans. Medical Imaging 32(1): 56-72 (2013) - [j9]Pablo Lamata
Quality Metrics for High Order Meshes: Analysis of the Mechanical Simulation of the Heart Beat. IEEE Trans. Medical Imaging 32(1): 130-138 (2013) - [c9]Pablo Lamata, Merzaka Lazdam, Anna Ashcroft, Adam J. Lewandowski, Paul Leeson, Nic Smith:
Computational Mesh as a Descriptor of Left Ventricular Shape for Clinical Diagnosis. CinC 2013: 571-574 - 2012
- [j8]Sebastian Krittian, Pablo Lamata
A finite-element approach to the direct computation of relative cardiovascular pressure from time-resolved MR velocity data. Medical Image Anal. 16(5): 1029-1037 (2012) - [c8]Oscar Camara
Integration of different cardiac electrophysiological models into a single simulation pipeline. ISBI 2012: 1429 - 2011
- [j7]Adinda Freudenthal, Thomas Stüdeli, Pablo Lamata
Collaborative co-design of emerging multi-technologies for surgery. J. Biomed. Informatics 44(2): 198-215 (2011) - [j6]Pablo Lamata
An accurate, fast and robust method to generate patient-specific cubic Hermite meshes. Medical Image Anal. 15(6): 801-813 (2011) - [c7]Jiahe Xi, Pablo Lamata
An Automatic Data Assimilation Framework for Patient-Specific Myocardial Mechanical Parameter Estimation. FIMH 2011: 392-400 - 2010
- [c6]Pablo Lamata
Generic Conduction Parameters for Predicting Activation Waves in Customised Cardiac Electrophysiology Models. STACOM/CESC 2010: 252-260 - [c5]Pablo Lamata
Personalization of Cubic Hermite Meshes for Efficient Biomechanical Simulations. MICCAI (2) 2010: 380-387
2000 – 2009
- 2008
- [j5]Pablo Lamata, Ashis Jalote-Parmar, Félix Lamata, Jérôme Declerck:
The Resection Map, a proposal for intraoperative hepatectomy guidance. Int. J. Comput. Assist. Radiol. Surg. 3(3-4): 299-306 (2008) - [j4]Pablo Lamata
Understanding Perceptual Boundaries in Laparoscopic Surgery. IEEE Trans. Biomed. Eng. 55(3): 866-873 (2008) - [c4]Alicia M. Cano, Francisco Gayá, Pablo Lamata
Laparoscopic Tool Tracking Method for Augmented Reality Surgical Applications. ISBMS 2008: 191-196 - 2007
- [j3]Pablo Lamata
SINERGIA laparoscopic virtual reality simulator: Didactic design and technical development. Comput. Methods Programs Biomed. 85(3): 273-283 (2007) - 2006
- [j2]Pablo Lamata
Conceptual Framework for Laparoscopic VR Simulators. IEEE Computer Graphics and Applications 26(6): 69-79 (2006) - [c3]Alicia M. Cano, Pablo Lamata
New Methods for Video-Based Tracking of Laparoscopic Tools. ISBMS 2006: 142-149 - 2004
- [c2]Pablo Lamata, Enrique J. Gómez, Francisco M. Sánchez-Margallo, Félix Lamata, Francisco Gayá, José B. Pagador, Jesús Usón, Francisco del Pozo:
Analysis of tissue consistency perception for laparoscopic simulator design. CARS 2004: 401-406 - [c1]Pablo Lamata, Enrique J. Gómez, Francisco M. Sánchez-Margallo
A New Methodology to Characterize Sensory Interaction for Use in Laparoscopic Surgery Simulation. ISMS 2004: 177-184 - 2003
- [j1]Alejandro F. Frangi
A registration-based approach to quantify Flow-Mediated Dilation (FMD) of the brachial artery in ultrasound image sequences. IEEE Trans. Medical Imaging 22(11): 1458-1469 (2003)
Coauthor Index
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last updated on 2024-10-22 20:15 CEST by the dblp team
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