The main areas of the CTARM group are algebraic reconstruction and motion compensation. An overview of the currently running projects is found right below.
Date | Responsible Person | Title | |
---|---|---|---|
27.01.2019 | Alexander Preuhs | Journal Club: Denoising CT with GANs | |
04.02.2019 | Qiuting Lee | MT final talk: Image registration of 2-D cone-beam mammography image and 3-D ultrasound image | |
11.02.2019 | Christoph Luckner | Journal Club: Convolutional Neural Network-based MAR in CT | |
04.03.2019 | all | Journal Club:Denoising for low dose CT | |
11.03.2019 | all | 2nd Journal Club, please read the paper! Denoising for low dose CT | |
29.04.2019 | Fasil Gadjimuradov | Final Talk: Concept and Realization of a Flexible Trajectory Generator with Data Completeness Analysis for Medical C-arm Robotic Systems | |
06.05.2019 | Lina Felsner | Intro to ADMM and ADMM for Limited Angle | |
17.05.2019 | all | ADMM with networks for CS-MRI | |
24.05.2019 | all | Internal Update Meeting | |
31.05.2019 | all | Internal Update Meeting | |
05.07.2019 | Alexander Preuhs | Talk: deep autofocus | |
12.07.2019 | Lina Felsner | BA Intro-Talk: Niklas Bubeck - Truncation-correction Method for X-ray Dark-field Computed Tomography | |
Gabriel Herl | Journal Club: Task-driven source–detector trajectories in cone-beam computed tomography: Part I and II. |
Mailing list subscription management page for students and guests.
We meet every Friday at 10:00h.
During renovation of our room (01.134-113), we temporarily meet in room 02.133-113.
Dynamic Cardiac Chamber Imaging in C-arm Computed TomographyThis project focuses on time-resolved volumetric reconstruction (i.e., 4-D imaging) of cardiac chambers from rotational angiography acquisitions. Two approaches are investigated: Motion-compensated analytic reconstruction as well as spatio-temporally regularized algebraic methods. |
Motion Compensation using Surface Information in CBCTThe focus of this project is to use surface information to compensate for motion in C-arm cone-beam CT. |
Motion Compensation in CBCT using Musculoskeletal ModelingThe goal of this project is to compensate for motion during C-arm cone-beam CT scans using a muskuloskeletal model based on inertial sensor data. |
Motion Compensation for DynaCT AcquisitionsThe focus of this project is the reconstruction of brain volumes acquired from patients suffering severe stroke using a C-arm system. Due to long acquisition times, standard reconstructions are corrupted by motion artifacts. |
Flow Quantification using 4D Digital Subtraction AngiographyThe goal of this project is to improve image quality of 4D DSA and estimate hemodynamic flow parameters from rotational angiography. |
Novel applications for twin-robotic X-ray imagingThis project will mainly focus on developing new clinically beneficial applications using a novel ceiling-mounted twin-robotic X-ray system. |
CONRADCONRAD is a software platform for simulation and reconstruction of flat-panel CT images. |
GPU based quantitative reconstruction in SPECT/CTGraphical Processing Units (GPU)s with their tremendous parallelity concept and computational power are being used in this project to develop novel quantitative reconstruction algorithms. |
Spatial-temporal Total Variation Regularization (STTVR) for 4D-CT Reconstruction4D-CT reconstruction based on compressed sensing. |
3-D Imaging of coronary vasculature using C-arm CTThe focus of this project is the optimisation of the 3-D reconstruction of coronary vasculature towards a quantitative representation. |
3-D Imaging of the heart chambers with C-arm CTIn this project, the focus of the 3-D reconstruction is on the left ventricle (LV). Regarding the long acquisition time of the C-arm system for the acquisition of the projection images (> 5s), the heart motion has to be considered. |
Perfusion C-arm CTPerfusion C-arm CT is a novel technology to measure capillary blood flow (CBF) with slowly rotating C-arm systems. |