SVF-Net: learning deformable image registration using shape matching
In this paper, we propose an innovative approach for registration based on the deterministic
prediction of the parameters from both images instead of the optimization of a energy …
prediction of the parameters from both images instead of the optimization of a energy …
A self-taught artificial agent for multi-physics computational model personalization
Personalization is the process of fitting a model to patient data, a critical step towards
application of multi-physics computational models in clinical practice. Designing robust …
application of multi-physics computational models in clinical practice. Designing robust …
Multifidelity-CMA: a multifidelity approach for efficient personalisation of 3D cardiac electromechanical models
Personalised computational models of the heart are of increasing interest for clinical
applications due to their discriminative and predictive abilities. However, the simulation of a …
applications due to their discriminative and predictive abilities. However, the simulation of a …
HELOP: Multi-target tracking based on heuristic empirical learning algorithm and occlusion processing
Y Jia, Y Zhang, C Zhou, Y Yang - Displays, 2023 - Elsevier
Multi-target tracking is one of the important fields in computer vision, which aims to solve the
problem of matching and correlating targets between adjacent frames. In this paper, we …
problem of matching and correlating targets between adjacent frames. In this paper, we …
Shape constraint function for artery tracking in ultrasound images
A Paris, A Hafiane - Computerized Medical Imaging and Graphics, 2021 - Elsevier
Ultrasound guided regional anesthesia (UGRA) has emerged as a powerful technique for
pain management in the operating theatre. It uses ultrasound imaging to visualize …
pain management in the operating theatre. It uses ultrasound imaging to visualize …
Method and system for image-based estimation of multi-physics parameters and their uncertainty for patient-specific simulation of organ function
A method and system for estimating tissue parameters of a computational model of organ
function and their uncertainty due to model assumptions, data noise and optimization …
function and their uncertainty due to model assumptions, data noise and optimization …
Automatic image-to-model framework for patient-specific electromechanical modeling of the heart
A key requirement for recent advances in computational modeling to be clinically applicable
is the ability to fit models to patient data. Various personalization techniques have been …
is the ability to fit models to patient data. Various personalization techniques have been …
Deep learning for robust segmentation and explainable analysis of 3d and dynamic cardiac images
Q Zheng - 2019 - theses.hal.science
Cardiac MRI is widely used by cardiologists as it allows extracting rich information from
images. However, if done manually, the information extraction process is tedious and time …
images. However, if done manually, the information extraction process is tedious and time …
Propagation of myocardial fibre architecture uncertainty on electromechanical model parameter estimation: a case study
Computer models of the heart are of increasing interest for clinical applications due to their
discriminative and predictive power. However the personalisation step to go from a generic …
discriminative and predictive power. However the personalisation step to go from a generic …
Multiple object tracking for video-based sports analysis
J Gudauskas, Ž Matusevičius - … studies 2021: Proceedings of the 26th …, 2021 - epubl.ktu.edu
Abstract [eng] Multiple object tracking (MOT) is a challenging task in computer vision. Many
algorithms have been proposed to track multiple targets for video surveillance, team-sport …
algorithms have been proposed to track multiple targets for video surveillance, team-sport …