11 citations · 38 across the 14 of their papers we have counts for
15 papers
ProPLIKS: Probablistic 3D human body pose estimation
Karthik Shetty, Annette Birkhold, Bernhard Egger +4
We present a novel approach for 3D human pose estimation by employing probabilistic modeling. This approach leverages the advantages of normalizing flows in non-Euclidean geometrie…
Physics-Informed Learning for Time-Resolved Angiographic Contrast Agent Concentration Reconstruction
Noah Maul, Annette Birkhold, Fabian Wagner +5
Three-dimensional Digital Subtraction Angiography (3D-DSA) is a well-established X-ray-based technique for visualizing vascular anatomy. Recently, four-dimensional DSA (4D-DSA) rec…
BOSS: Bones, Organs and Skin Shape Model
Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan +4
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 trackin…
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model
Noah Maul, Katharina Zinn, Fabian Wagner +6
Patient-specific hemodynamics assessment could support diagnosis and treatment of neurovascular diseases. Currently, conventional medical imaging modalities are not able to accurat…
PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation
Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan +4
We introduce PLIKS (Pseudo-Linear Inverse Kinematic Solver) for reconstruction of a 3D mesh of the human body from a single 2D image. Current techniques directly regress the shape,…
Deep Learning compatible Differentiable X-ray Projections for Inverse Rendering
Karthik Shetty, Annette Birkhold, Norbert Strobel +4
Many minimally invasive interventional procedures still rely on 2D fluoroscopic imaging. Generating a patient-specific 3D model from these X-ray projection data would allow to impr…
X-ray Scatter Estimation Using Deep Splines
Philipp Roser, Annette Birkhold, Alexander Preuhs +7
Algorithmic X-ray scatter compensation is a desirable technique in flat-panel X-ray imaging and cone-beam computed tomography. State-of-the-art U-net based image translation approa…
Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning
Philipp Roser, Xia Zhong, Annette Birkhold +7
Scattered radiation is a major concern impacting X-ray image-guided procedures in two ways. First, back-scatter significantly contributes to patient (skin) dose during complicated…
Pitfalls in interventional X-ray organ dose assessment -- combined experimental and computational phantom study: application to prostatic artery embolization
Philipp Roser, Annette Birkhold, Xia Zhong +5
With X-ray radiation protection and dose management constantly gaining interest in interventional radiology, novel procedures often undergo prospective dose studies using anthropom…
Effects of Tissue Material Properties on X-Ray Image, Scatter and Patient Dose Determined using Monte Carlo Simulations
Philipp Roser, Annette Birkhold, Xia Zhong +4
With increasing patient and staff X-ray radiation awareness, many efforts have been made to develop accurate patient dose estimation methods. To date, Monte Carlo (MC) simulations…
Fully-automatic CT data preparation for interventional X-ray skin dose simulation
Philipp Roser, Annette Birkhold, Alexander Preuhs +6
Recently, deep learning (DL) found its way to interventional X-ray skin dose estimation. While its performance was found to be acceptable, even more accurate results could be achie…
Tenfold your photons -- a physically-sound approach to filtering-based variance reduction of Monte-Carlo-simulated dose distributions
Philipp Roser, Annette Birkhold, Alexander Preuhs +3
X-ray dose constantly gains interest in the interventional suite. With dose being generally difficult to monitor reliably, fast computational methods are desirable. A major drawbac…
Deep Scatter Splines: Learning-Based Medical X-ray Scatter Estimation Using B-splines
Philipp Roser, Annette Birkhold, Alexander Preuhs +5
The idea of replacing hardware by software to compensate for scattered radiation in flat-panel X-ray imaging is well established in the literature. Recently, deep-learningbased ima…
Decoding the Rejuvenating Effects of Mechanical Loading on Skeletal Maturation using in Vivo Imaging and Deep Learning
Pouyan Asgharzadeh, Oliver Röhrle, Bettina M. Willie +1
Throughout the process of aging, deterioration of bone macro- and micro-architecture, as well as material decomposition result in a loss of strength and therefore in an increased l…
Action Learning for 3D Point Cloud Based Organ Segmentation
Xia Zhong, Mario Amrehn, Nishant Ravikumar +6
We propose a novel point cloud based 3D organ segmentation pipeline utilizing deep Q-learning. In order to preserve shape properties, the learning process is guided using a statist…