250 citations · 534 across the 17 of their papers we have counts for
18 papers
A multi-organ point cloud registration algorithm for abdominal CT registration
Samuel Joutard, Thomas Pheiffer, Chloe Audigier +6
Registering CT images of the chest is a crucial step for several tasks such as disease progression tracking or surgical planning. It is also a challenging step because of the heter…
Automated Catheter Tip Repositioning for Intra-cardiac Echocardiography
Young-Ho Kim, Jarrod Collins, Zhongyu Li +4
Purpose: Intra-Cardiac Echocardiography (ICE) is a powerful imaging modality for guiding cardiac electrophysiology and structural heart interventions. ICE provides real-time observ…
Shape-adaptive Hysteresis Compensation for Tendon-driven Continuum Manipulators
Young-Ho Kim, Tommaso Mansi
Tendon-driven continuum manipulators (TDCM) are commonly used in minimally invasive surgical systems due to their long, thin, flexible structure that is compliant in narrow or tort…
A Wide-area, Low-latency, and Power-efficient 6-DoF Pose Tracking System for Rigid Objects
Young-Ho Kim, Ankur Kapoor, Tommaso Mansi +1
Position sensitive detectors (PSDs) offer possibility to track single active marker's two (or three) degrees of freedom (DoF) position with a high accuracy, while having a fast res…
Non-linear Hysteresis Compensation of a Tendon-sheath-driven Robotic Manipulator using Motor Current
Dong-Ho Lee, Young-Ho Kim, Jarrod Collins +3
Tendon-sheath-driven manipulators (TSM) are widely used in minimally invasive surgical systems due to their long, thin shape, flexibility, and compliance making them easily steerab…
Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix
Julian Krebs, Hervé Delingette, Nicholas Ayache +1
We propose to learn a probabilistic motion model from a sequence of images for spatio-temporal registration. Our model encodes motion in a low-dimensional probabilistic space - the…
Graph convolutional regression of cardiac depolarization from sparse endocardial maps
Felix Meister, Tiziano Passerini, Chloé Audigier +6
Electroanatomic mapping as routinely acquired in ablation therapy of ventricular tachycardia is the gold standard method to identify the arrhythmogenic substrate. To reduce the acq…
Towards Automatic Manipulation of Intra-cardiac Echocardiography Catheter
Young-Ho Kim, Jarrod Collins, Zhongyu Li +4
Intra-cardiac Echocardiography (ICE) is a powerful imaging modality for guiding electrophysiology and structural heart interventions. ICE provides real-time observation of anatomy,…
Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI
Julian Krebs, Tommaso Mansi, Nicholas Ayache +1
We propose to learn a probabilistic motion model from a sequence of images. Besides spatio-temporal registration, our method offers to predict motion from a limited number of frame…
Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations
Chen Qin, Bibo Shi, Rui Liao +3
We propose a fully unsupervised multi-modal deformable image registration method (UMDIR), which does not require any ground truth deformation fields or any aligned multi-modal imag…
Towards Fast Biomechanical Modeling of Soft Tissue Using Neural Networks
Felix Meister, Tiziano Passerini, Viorel Mihalef +3
To date, the simulation of organ deformations for applications like therapy planning or image-guided interventions is calculated by solving the elastodynamics equations. While effi…
Learning a Probabilistic Model for Diffeomorphic Registration
Julian Krebs, Hervé Delingette, Boris Mailhé +2
We propose to learn a low-dimensional probabilistic deformation model from data which can be used for registration and the analysis of deformations. The latent variable model maps…
Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation
Yue Zhang, Shun Miao, Tommaso Mansi +1
Automatic parsing of anatomical objects in X-ray images is critical to many clinical applications in particular towards image-guided invention and workflow automation. Existing dee…
Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration
Julian Krebs, Tommaso Mansi, Boris Mailhé +2
We propose a deformable registration algorithm based on unsupervised learning of a low-dimensional probabilistic parameterization of deformations. We model registration in a probab…
Dilated FCN for Multi-Agent 2D/3D Medical Image Registration
Shun Miao, Sebastien Piat, Peter Fischer +4
2D/3D image registration to align a 3D volume and 2D X-ray images is a challenging problem due to its ill-posed nature and various artifacts presented in 2D X-ray images. In this p…
An Artificial Agent for Robust Image Registration
Rui Liao, Shun Miao, Pierre de Tournemire +4
3-D image registration, which involves aligning two or more images, is a critical step in a variety of medical applications from diagnosis to therapy. Image registration is commonl…
Shaping the Future through Innovations: From Medical Imaging to Precision Medicine
Dorin Comaniciu, Klaus Engel, Bogdan Georgescu +1
Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information rep…
A Self-Taught Artificial Agent for Multi-Physics Computational Model Personalization
Dominik Neumann, Tommaso Mansi, Lucian Itu +10
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…