Developing Image Processing Techniques for Cryo Electron Tomography In medical collaboration with: Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. Scientific Director: Nassir Navab Contact Person(s): Shadi Albarqouni

Keywords: Reconstruction, Molecular Imaging, Machine Learning for Medical Applications, Microscopic Image Analysis

Abstract

Cryo-ET has recently emerged as a leading technique to investigate the three-dimensional(3D) structure of biological specimens at close-to-native state. It also bridges the gap between low-resolution imaging techniques (e.g. light microscopy) and high-resolution techniques (e.g. single particle electron microscopy). The technique consists of acquiring many two-dimensional (2D) projections of the structure under scrutiny at various tilt angles under cryogenic conditions. The 3D structure is recovered through a number of steps including projection alignment, reconstruction and de-nosing. The resolution of the reconstructed tomogram, however, is aaffected by the low signal to noise ratio (SNR) of the projection images (typically 0.1 to 0.01) and the limited angular coverage (typically 60  to 70 ) resulting in wedge-shaped missing information in Fourier space, the so-called missing wedge; making the reconstruction process very challenging and demanding.

Team

Contact Person(s)

Dr. Shadi Albarqouni

Working Group

Dr. Maximilian Baust

Dr. Shadi Albarqouni

PD Tobias Lasser

Location

Technische Universität München Institut für Informatik / I16 Boltzmannstr. 3 85748 Garching bei München Tel.: +49 89 289-17058 Fax: +49 89 289-17059

Visit our lab at Garching.



internal project page

Please contact Shadi Albarqouni for available student projects within this research project.

The following presentation is a simple overview of the whole image processing pipeline in CryoET^?.

Project Phases

Date	Topic	Conducted by	Materials
Feb. 2014	Gradient Projection for Regularized Cryo-Electron Tomographic Reconstruction		CMMI-MICCAI Paper
Oct. 2014	Image Denoising in High Dimensional Space	MLMI Group	Project webpage
Feb. 2015	Multi-scale Graph-based Guided Filter for De-noising Cryo-Electron Tomographic Data (MG2F)	Shadi	BMVC Paper, BMVC Poster, Toy Example
Jun. 2015	RISE Internship	Claire	TBA