We describe an algorithm for 3D interactive image segmenta- tion by non-rigid implicit template deformation, with two main original features. First, our formulation incorporates user input as inside/outside labeled points to drive the deformation and improve both robustness and accuracy. This yields inequality constraints, solved using an Augmented Lagrangian approach. Secondly, a fast implementation of non-rigid template-to-image registration enables interactions with a real-time visual feedback. We validated this generic technique on 21 Contrast-Enhanced Ultrasound images of kidneys and obtained accurate segmentation results (Dice> 0:93) in less than 3 clicks in average
As computers can only represent and process discrete data, information gathered from the real world...
International audienceCreating and animating subject-specific anatomical models is traditionally a d...
We propose a new algorithm for two-phase, piecewise-smooth segmentation with shape prior. The image ...
Abstract. Implicit template deformation is a model-based segmenta-tion framework that was successful...
Implicit template deformation is a model-based segmentation framework that was successfully applied ...
Abstract. Implicit template deformation is a model-based segmenta-tion framework that was successful...
Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate mo...
International audience<p>We present a new method for the segmentation of multipleorgans (2D or 3D) w...
INTRODUCTION The segmentation of 3D diagnostic images is important in quantifying and visualising t...
International audienceIn this paper we address the problem of extracting geometric models from low c...
EI 2016 : IS&T International Symposium on Electronic Imaging , Feb 14-18, 2016 , San Francisco , CA ...
Abstract Contrast-enhanced ultrasound (CEUS) imaging has lately benefited of an increasing interest ...
We present an interactive segmentation method for 3D medical images that reconstructs the surface of...
We present an interactive segmentation method for three-dimensional medical images that reconstructs...
There are many approaches to weakly-supervised training of networks to segment 2D images. By contras...
As computers can only represent and process discrete data, information gathered from the real world...
International audienceCreating and animating subject-specific anatomical models is traditionally a d...
We propose a new algorithm for two-phase, piecewise-smooth segmentation with shape prior. The image ...
Abstract. Implicit template deformation is a model-based segmenta-tion framework that was successful...
Implicit template deformation is a model-based segmentation framework that was successfully applied ...
Abstract. Implicit template deformation is a model-based segmenta-tion framework that was successful...
Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate mo...
International audience<p>We present a new method for the segmentation of multipleorgans (2D or 3D) w...
INTRODUCTION The segmentation of 3D diagnostic images is important in quantifying and visualising t...
International audienceIn this paper we address the problem of extracting geometric models from low c...
EI 2016 : IS&T International Symposium on Electronic Imaging , Feb 14-18, 2016 , San Francisco , CA ...
Abstract Contrast-enhanced ultrasound (CEUS) imaging has lately benefited of an increasing interest ...
We present an interactive segmentation method for 3D medical images that reconstructs the surface of...
We present an interactive segmentation method for three-dimensional medical images that reconstructs...
There are many approaches to weakly-supervised training of networks to segment 2D images. By contras...
As computers can only represent and process discrete data, information gathered from the real world...
International audienceCreating and animating subject-specific anatomical models is traditionally a d...
We propose a new algorithm for two-phase, piecewise-smooth segmentation with shape prior. The image ...