Tomography and Instrumentation

Group leader: D. Stsepankou



  • Auto-calibration for Dental CBCT

The image quality of a dental cone-beam computed tomography (CBCT) is limited by the accuracy of device calibration. Incorrect calibration introduces errors in the reconstruction process, which lead to severe artifacts in the reconstructed volume. Possible patient movement during scan acquisition induces similar effects. In the frame of this project we develop an auto-calibration routine which calculates the geometrical projection parameters from unknown patient geometry. We formulate consistency conditions linking the information of consecutive projection images and a regularization technique to prevent overall distortions. We derive a global optimization problem and a greedy optimizer herein. Our strategy is robust towards inaccurate initialization as it is involves an iterative approach regarding calibration accuracy. As our method does not rely on consistency between projection data and tomography reconstruction it is robust towards truncation as well.
  •  Development of optimization techniqe for optimal positioning of the Laserspots in refractive surgery

In the realm of refractive surgery, and irrespective of the surgical modality, a smoother corneal surface post ablation shall always result in better outcomes compared to a rougher surface post ablation. A post-operative rough corneal surface can have a deleterious influence on immediate outcomes, patient confidence, short term outcomes (even affecting long term outcomes in some cases), levels of postoperative visual acuity, reepithelization time, pain sensation in surface ablation procedures, levels of the induced aberrations (especially the so called higher order aberrations), and flap quality interface.  The goal of this project is to develop the optimization technique for positioning laserspots during the surgery such that the resulted roughness of the surface is mimimal. 


  • Modeling the SIGMA-Eye Applicator for Hyperthermia 

Hyperthermia treatment is a cancer therapy where tissues are exposed to high temperatures (45oC) to sensitize and kill tumor cells. Hyperthermia is classified into different types according to target regions and method of generating heat. In this project deep regional electromagnetic hyperthermia is considered, which aims at deep-seated tumors, e.g. of the pelvis or abdomen, and is driven by electromagnetic waves. Driven by recent progress in computing power and numerical techniques personalized hyperthermia treatment planning (HTP) is becoming possible for clinical practice. Electromagnetic hyperthermia treatment planning (EM-HTP) is divided into six basic steps, including image data (CT or MRI) acquisition, image segmentation, treatment model creation, electromagnetic simulation (EM simulation), temperature simulation and optimization. EM simulation is the process of modelling the interaction of electromagnetic fields with physical objects. In theory, Maxwell’s Equations describe how an electromagnetic field propagates in media. Hence, EM simulation requires numerically solving these partial differential equations. The objective of this project is to investigate the applicability of Infinitesimal Dipole Model  for the phased-array the SIGMA-Eye applicator in EM simulation for the treatment planning for deep-regional electromagnetic hyperthermia treatment.


  •          Computer Tomography Framework

          We are developing a framework for computer tomography. This framework consists of several elements: 
  • Efficient GPU-implementation of all modern iterative and non-iterative reconstruction techniques.
  • New, non-linear sparsity regularizers like Anisotropic Total Variation (ATV) [1], combined first order ATV and second order TV [2]  and Generalized Anisotropic Total Variation (GATV) [3] for accurate , low-dose iterative CT reconstruction from few projections.
  • Accurate forward and backward modeling using the footprint method.
  • Tools for estimating projection matrices from image data.
  • Calibration tools and software for cone-beam CT systems.
  • Dosimetric tools for cone-beam CT systems.
  • GPU-based MC simulators.
  • New and fast optimizers for computed tomography.
  • Multi-energy reconstruction using kV and MV energies.
  • Publications: [1] [2] [3] [4] [5] [6] [7]