The presentation of this work was made at PhD Student AACEE competition 2018, in Bratislava at Slovak University of Technology This work was motivated by the Atlas-based segmentation (ABS) method, where we find the correspondences between shapes used in the atlas construction. The contribution the previous work are Extension of shape registration method to 3D data. Representation of the shapes using distance map function. Using gradient descent methods to find the optimal Affine transformation in the optimization criterion. Efficiency improvements through Using Stochastic Gradient Descent method Parallelization of the distance map algorithm using graphics processing uni
This paper presents a method for vote-based 3D shape recognition and registration, in particular usi...
Statistical shape models (SSMs) are a well-established tool in medical image analysis. The most chal...
Statistical shape models (SSMs) are a well-established tool in medical image analysis. The most chal...
The presentation of this work was made at PhD Student AACEE competition 2018, in Bratislava at Slova...
Abstract—In this paper, a novel method to solve the shape registration problem covering both global ...
The image segmentation algorithm extending Geodesic Active Contours method by an influence of prior ...
We describe a robust method for spatial registration, which relies on the coarse correspondence of s...
We describe a modification to distance based transforms used for non–linear registration, such as ra...
Much biomedical and medical research relies on the collection of ever-larger amounts of image data (...
Many spatial datasets and spatial problems can be described with reference to regular lattice framew...
Atlas-based segmentation is an increasingly popular method of automatically computing a segmentation...
International audienceThis article deals with statistics on sets of shapes. The approach is based on...
Geometric shapes can be represented in a variety of different ways. A distancemap is a map from poin...
• Given a set of corresponding points in 2 frames, find a “global map” (usually a group action) that...
Abstract: A distance transform, also known as distance map or distance field, is a representation of...
This paper presents a method for vote-based 3D shape recognition and registration, in particular usi...
Statistical shape models (SSMs) are a well-established tool in medical image analysis. The most chal...
Statistical shape models (SSMs) are a well-established tool in medical image analysis. The most chal...
The presentation of this work was made at PhD Student AACEE competition 2018, in Bratislava at Slova...
Abstract—In this paper, a novel method to solve the shape registration problem covering both global ...
The image segmentation algorithm extending Geodesic Active Contours method by an influence of prior ...
We describe a robust method for spatial registration, which relies on the coarse correspondence of s...
We describe a modification to distance based transforms used for non–linear registration, such as ra...
Much biomedical and medical research relies on the collection of ever-larger amounts of image data (...
Many spatial datasets and spatial problems can be described with reference to regular lattice framew...
Atlas-based segmentation is an increasingly popular method of automatically computing a segmentation...
International audienceThis article deals with statistics on sets of shapes. The approach is based on...
Geometric shapes can be represented in a variety of different ways. A distancemap is a map from poin...
• Given a set of corresponding points in 2 frames, find a “global map” (usually a group action) that...
Abstract: A distance transform, also known as distance map or distance field, is a representation of...
This paper presents a method for vote-based 3D shape recognition and registration, in particular usi...
Statistical shape models (SSMs) are a well-established tool in medical image analysis. The most chal...
Statistical shape models (SSMs) are a well-established tool in medical image analysis. The most chal...