Publications related to Active Deformation Fields: Dense Deformation Field Estimation for Atlas-based Segmentation using the Active Contour Framework

Related publications (30)

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

Semantic segmentation for remote sensing images (RSI) is critical for the Earth monitoring system. However, the covariate shift between RSI datasets under different capture conditions cannot be alleviated by directly using the unsupervised domain adaptatio ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

A deep learning framework for matching of SAR and optical imagery

Devis Tuia, Lloyd Haydn Hughes

SAR and optical imagery provide highly complementary information about observed scenes. A combined use of these two modalities is thus desirable in many data fusion scenarios. However, any data fusion task requires measurements to be accurately aligned. Wh ...

2020

Automated CT bone segmentation using statistical shape modelling and local template matching

Alexandre Terrier, Alain Farron, Philippe Büchler

Accurate CT bone segmentation is essential to develop chair-side manufacturing of implants based on additive manufacturing. We herewith present an automated method able to accurately segment challenging bone regions, while simultaneously providing anatomic ...

2019

Landmark-Based Shape Encoding and Sparse-Dictionary Learning in the Continuous Domain

Michaël Unser, Daniel Andreas Schmitter

We provide a generic framework to learn shape dictionaries of landmark-based curves that are defined in the continuous domain. We first present an unbiased alignment method that involves the construction of a mean shape as well as training sets whose eleme ...

2018

Modeling Facial Geometry using Compositional VAEs

Pascal Fua, Timur Bagautdinov

We propose a method for learning non-linear face geometry representations using deep generative models. Our model is a variational autoencoder with multiple levels of hidden variables where lower layers capture global geometry and higher ones encode more l ...

2018

A Compressed Sensing Approach for Distribution Matching

Vahid Aref, Mohamad Baker Dia

In this work, we formulate the fixed-length distribution matching as a Bayesian inference problem. Our proposed solution is inspired from the compressed sensing paradigm and the sparse superposition (SS) codes. First, we introduce sparsity in the binary so ...

IEEE2018

Spline Shape Processing : Representation, Learning, and Modeling

Daniel Andreas Schmitter

In this thesis, we present a novel generic and unifying framework for data-adaptive shape modeling. Our work is motivated by the raising need for powerful geometric modeling kernels that are required for shape characterization in biomedical imaging. The on ...

EPFL2017

Template-based Monocular 3-D Shape Reconstruction And Tracking Using Laplacian Meshes

Tien Dat Ngo

This thesis addresses the problem of recovering the 3-D shape of a deformable object in single images, or image sequences acquired by a monocular video camera, given that a 3-D template shape and a template image of the object are available. While being a ...

EPFL2016

Distribution-Matching Embedding for Visual Domain Adaptation

Mathieu Salzmann

Domain-invariant representations are key to addressing the domain shift problem where the training and test examples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typical ...

2016

Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization

Alfio Quarteroni, Gianluigi Rozza, Andrea Manzoni, Elena Faggiano

In this work a reduced-order computational framework for the study of haemodynamics in three-dimensional patient-specific configurations of coronary artery bypass grafts dealing with a wide range of scenarios is proposed. We combine several efficient algor ...

Elsevier2016

Template-free 3D Reconstruction of Poorly-textured Nonrigid Surfaces

Mathieu Salzmann, Xinchao Wang

Two main classes of approaches have been studied to perform monocular nonrigid 3D reconstruction: Template-based methods and Non-rigid Structure from Motion techniques. While the first ones have been applied to reconstruct poorly-textured surfaces, they as ...

Springer Int Publishing Ag2016

Smoothly Deformable Spheres: Modeling, Deformation, and Interaction

Michaël Unser, Daniel Andreas Schmitter

Existing shape models with spherical topology are typically designed either in the discrete domain using interpolating polygon meshes or in the continuous domain using smooth but non-interpolating schemes such as NURBS. Polygon models and subdivision metho ...

ACM2016

Shape-Selective Assembly of Anisotropic, Deformable Microcomponents Using Bottom-Up Micromanufacturing

Gunjan Agarwal

A technique for shape-selective directed assembly of anisotropic, deformable, chemically-identical microcomponents onto patterned rigid templates based on shape and size differences is modeled and demonstrated. The assembly method not only controls the sel ...

Mdpi Ag2016

Dense image registration and deformable surface reconstruction in presence of occlusions and minimal texture

Pascal Fua, Alberto Crivellaro, Tien Dat Ngo, Anne Alison Jorstad

Deformable surface tracking from monocular images is well-known to be under-constrained. Occlusions often make the task even more challenging, and can result in failure if the surface is not sufficiently textured. In this work, we explicitly address the pr ...

2015

Image processing on reconfigurable hardware for continuous monitoring of fluorescent biomarkers in cell cultures

Julien Michel Ghaye

Fluorescence microscopy is a widespread tool in biological research. It is the primary modality for bioimaging and empowers the study and analysis of multitudes of biological processes. It can be applied to fixed biosamples, that is samples with frozen bio ...

EPFL2015

Transformation-Invariant Analysis of Visual Signals with Parametric Models

Elif Vural

The analysis of collections of visual data, e.g., their classification, modeling and clustering, has become a problem of high importance in a variety of applications. Meanwhile, image data captured in uncontrolled environments by arbitrary users is very li ...

EPFL2013

Weighted Shape-Based Averaging With Neighborhood Prior Model for Multiple Atlas Fusion-Based Medical Image Segmentation

Jean-Philippe Thiran, Meritxell Bach Cuadra, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: “Global Weighted Shape-Based Averaging” (GWSBA) and “Local Weig ...

IEEE Institute of Electrical and Electronics Engineers2013

Spline-Based Deforming Ellipsoids for Interactive 3D Bioimage Segmentation

Michaël Unser, Ricard Delgado Gonzalo

We present a new fast active-contour model (a.k.a. snake) for image segmentation in 3D microscopy. We introduce a parametric design that relies on exponential B-spline bases and allows us to build snakes that are able to reproduce ellipsoids. We design our ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Cell-Based Deformation Monitoring via 3D Point Clouds

Jing Wu

Deformation is one of the most important phenomena in environmental science and engineering. Deformation of artificial and natural objects happens worldwide, such as structural deformation, landslide, subsidence, erosion, and rockfall. Monitoring and asses ...

EPFL2012

Computing correspondences in geometric data sets

Mark Pauly, Hao Li

Shape registration and, more generally speaking, computing correspondence across shapes are fundamental problems in computer graphics and vision. Problems from this area show up in many diff erent variants such as scan registration, deformable shape matchi ...

2011