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Found 13 papers, 2 papers with code
Physics-Informed Learning for Time-Resolved Angiographic Contrast Agent Concentration Reconstruction
In our work, we implicitly include this information in a neural network-based model that is trained on a dataset of image-based blood flow simulations.
BOSS: Bones, Organs and Skin Shape Model
Objective: A digital twin of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless tracking, positioning, and navigation assistance in image-guided interventions.
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model
Nevertheless, the prediction of high-resolution transient CFD simulations for complex vascular geometries poses a challenge to conventional deep learning models.
PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation
Current techniques directly regress the shape, pose, and translation of a parametric model from an input image through a non-linear mapping with minimal flexibility to any external influences.
Ranked #2 on
3D Human Pose Estimation
on 3DPW
(using extra training data)
Deep Learning compatible Differentiable X-ray Projections for Inverse Rendering
First, a statistical human shape model of the human anatomy and second, a differentiable X-ray renderer.
Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning
Here, we propose a novel approach combining conventional techniques with learning-based methods to simultaneously estimate the forward-scatter reaching the detector as well as the back-scatter affecting the patient skin dose.
Appearance Learning for Image-based Motion Estimation in Tomography
To this end, we train a siamese triplet network to predict the reprojection error (RPE) for the complete acquisition as well as an approximate distribution of the RPE along the single views from the reconstructed volume in a multi-task learning approach.
Deep autofocus with cone-beam CT consistency constraint
To adapt the backprojection operation accordingly, a motion estimation strategy is necessary.
Image Quality Assessment for Rigid Motion Compensation
Diagnostic stroke imaging with C-arm cone-beam computed tomography (CBCT) enables reduction of time-to-therapy for endovascular procedures.
A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems
Nevertheless, publications introducing novel interactive segmentation systems (ISS) often lack an objective comparison of HCI aspects.
Action Learning for 3D Point Cloud Based Organ Segmentation
From this we conclude that our method is robust, and we believe that our method can be successfully applied to many more applications, in particular, in the interventional imaging space.
Robust Seed Mask Generation for Interactive Image Segmentation
In interactive medical image segmentation, anatomical structures are extracted from reconstructed volumetric images.
UI-Net: Interactive Artificial Neural Networks for Iterative Image Segmentation Based on a User Model
Our system builds upon a state-of-the-art fully convolutional artificial neural network (FCN) as well as an active user model for training.
