Search Results for author:
Found 11 papers, 1 papers with code
Spatio-temporal reconstruction of substance dynamics using compressed sensing in multi-spectral magnetic resonance spectroscopic imaging
The objective of our study is to observe dynamics of multiple substances in vivo with high temporal resolution from multi-spectral magnetic resonance spectroscopic imaging (MRSI) data.
Shape Reconstruction from Thoracoscopic Images using Self-supervised Virtual Learning
To address the uncertainty in reconstructing entire shapes from single-viewpoint occluded images, we propose a framework for generative virtual learning of shape reconstruction using image translation with common latent variables between simulated and real images.
2D/3D Deep Image Registration by Learning 3D Displacement Fields for Abdominal Organs
Deformable registration of two-dimensional/three-dimensional (2D/3D) images of abdominal organs is a complicated task because the abdominal organs deform significantly and their contours are not detected in two-dimensional X-ray images.
Feedback Assisted Adversarial Learning to Improve the Quality of Cone-beam CT Images
Unsupervised image translation using adversarial learning has been attracting attention to improve the image quality of medical images.
IGCN: Image-to-graph Convolutional Network for 2D/3D Deformable Registration
Organ shape reconstruction based on a single-projection image during treatment has wide clinical scope, e. g., in image-guided radiotherapy and surgical guidance.
Kernel-based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks
In video-assisted thoracoscopic surgeries, successful procedures of nodule resection are highly dependent on the precise estimation of lung deformation between the inflated lung in the computed tomography (CT) images during preoperative planning and the deflated lung in the treatment views during surgery.
Statistical modeling of pneumothorax deformation by mapping CT and cone-beam CT images
In this study, we introduce statistical modeling methods for pneumothorax deformation using paired cone-beam computed tomography (CT) images.
Computed Tomography (CT)
Computational Geometry
Numerical Analysis
Numerical Analysis
Three-dimensional Generative Adversarial Nets for Unsupervised Metal Artifact Reduction
The reduction of metal artifacts in computed tomography (CT) images, specifically for strong artifacts generated from multiple metal objects, is a challenging issue in medical imaging research.
Statistical Deformation Reconstruction Using Multi-organ Shape Features for Pancreatic Cancer Localization
In this paper, we introduce a multi-organ deformation library and its application to deformation reconstruction based on the shape features of multiple abdominal organs.
Sparse Elasticity Reconstruction and Clustering using Local Displacement Fields
This paper introduces an elasticity reconstruction method based on local displacement observations of elastic bodies.
Deformation estimation of an elastic object by partial observation using a neural network
Deformation estimation of elastic object assuming an internal organ is important for the computer navigation of surgery.
