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Population Modelling

The population modelling group is dedicated to analyse data collected from many individuals in order to be able to model variations within entire populations.

Colloquium Time Table

Responsible PersonTitle

Abdurrahman Becit

Philipp Roser

Master Thesis Final Talk: Cell Tracking using Image Registration

Master Thesis Intro: Estimation and Visualization of Skin Dose in an Interventional Environment using Machine Learning 

07.11.2017Xia Zhong

Journal Club: Opens external link in new windowTowards robust and effective shape modeling: sparse shape composition, Opens external link in new windowTMI Issue 11, Nov. 2017

21.11.2017Juergen EndresJournal Club: MedPhys Issue 11, Nov. 2017; PMB Nbr. 22, Nov. 2017
05.12.2017Shuqing Chen

Journal Club: Manifold Learning for Medical Image Registration, Segmentation, and Classification 

09.01.2018Philipp RoserMaster Thesis Final: Estimation and Visualization of Skin Dose in an Interventional Environment using Machine Learning 
06.02.2018Xia ZhongJournal Club: Opens external link in new windowAutomatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields


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Running Projects

X-Ray Imaging Using a Patient Model

This project focuses on estimate a patient model and model based X-ray imaging application. The current research focus is on anatomical patient modelling and model based skin and scatter estimation.

Quantitative DECT with prior atlas knowledge

This project aims at decomposing the materials with anatomy knowledge automatically. An atlas provides the prior knowledge - the anatomic structures. The anatomy knowledge allows then automatic decomposition and classification of the different materials.

Quantification and Respiratory Motion Management for SPECT Imaging

Population-based metrics for diagnosis and patient stratification are important aids for nuclear medicine physicians when dealing with various cardiological, neurological, and oncological indications. A necessary input to such approaches based on SPECT is a standardized, artifact-free dataset. The goals of this project include improvement of standardization through quantitative imaging and reduction of respiratory motion artifacts through data-driven techniques.

Finished Projects

Time-of-Flight 4-D Foot Scan

3-D Reconstruction of the shape of human feet during motion.

Attenuation Correction for Hybrid Imaging Systems

Attenuation maps for correcting PET data needs to be derived from MR information in current PET/MR hybrid systems

Catheter Contact Force

Catheter contact force assessment and evaluation for cardiac ablation procedures.

Motion Compensation

Cardiac and respiratory motion compensation for atrial fibrillation ablation procedures.