Search


Robust Scattered Data Points Approximation Using Finite Element Biomechanical Model
starstarstarstarstar
Many enabling technologies like non-rigid registration in medical image computing rely on the construction of a function by interpolating scattered points; however, the outliers contained in the data and the approximation error make the robust and accurate [...]

Simulation of Active Cardiac Dynamics with Orthotropic Hyperelastic Material Model
starstarstarstarstar
Meaningful physical models are important for studying cardiac physiology, such as quantitative assessments of pathology via changes in model parameters, and recovering information from medical images. In order to achieve realistic deformation studies, an [...]

An ITK Implementation of Physics-based Non-rigid Registration Method
starstarstarstarstar
As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid [...]

A semi-automated method for liver tumor segmentation based on 2D region growing with
starstarstarstarstar
Liver tumour segmentation from computed tomography (CT) scans is a challenging task. A semi-automatic method based on 2D region growing with knowledge-based constraints is proposed to segment lesions from constituent 2D slices obtained from 3D CT images. [...]

Semi-automatic Segmentation of Liver Tumors from CT Scans Using Bayesian Rule-based 3D Region Growing
starstarstarstarstar
Automatic segmentation of liver tumorous regions often fails due to high noise and large variance of tumors. In this work, a semi-automatic algorithm is proposed to segment liver tumors from computed tomography (CT) images. To cope with the variance of [...]

Semi-automatic Segmentation of 3D Liver Tumors from CT Scans Using Voxel Classification and Propagational Learning
starstarstarstarstar
A semi-automatic scheme was developed for the segmentation of 3D liver tumors from computed tomography (CT) images. First a support vector machine (SVM) classifier was trained to extract tumor region from one single 2D slice in the intermediate part of a [...]

Segmentation of the Left Ventricle from Cine MR Images Using a Comprehensive Approach
No opinion
Segmentation of the left ventricle is important in assessment of cardiac functional parameters. Currently, manual segmentation is the gold standard for acquiring these parameters and can be time-consuming. Therefore, accuracy and automation are two important [...]


Sort results by

Refine the search results

Keywords

Authors

main_flat
Powered by Midas