Finished projects


ML-X-RAY - Machine learning and X-ray technology for measuring inhomogeneous cable and pipe products

Duration: 01.03.2021 - 31.10.2022
PI: Peter Maaß

In production engineering, the purity of a product and the associated quality control play a central role. To ensure maximum material and cost savings, the reliable measurement of the manufactured products as well as the detection of deviations with regard to the given product specification is indispensable. The aim of ML-X-RAY is the further development of a measuring system for the inspection of inhomogeneous cable and pipe products with the help of innovative approaches from the field of Machine Learning or Deep Learning in the form of Convolutional Neural Networks. The project is being carried out in cooperation with the industrial partner SIKORA AG.

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SFB 1232 From colored states to evolutionary structural materials

Duration: 01.07.2016 - 30.06.2020
PI: Peter Maaß

Whether it is the energy revolution or mobility: the demands on metallic materials of the future are growing, and their development is now playing a key role. It is fundamental to adapt the properties of the materials accordingly to the specific requirements. The selection of the most suitable alloy compositions and the adjustment of the corresponding crystals open up complex and diverse search spaces.

MPI Relaxation

MPI² - Model-based parameter identification in Magnetic Particle Imaging

Duration: 01.12.2016 - 31.05.2020
PIs: Peter Maaß, Tobias Kluth

In MPI², model-based methods and their efficient algorithmic implementation are explored. Magnetic particle imaging (MPI), a tomographic method based on tracking iron oxide nanoparticles in the human body, serves here as an application example.

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MaDiPath - Mass spectrometric profiling/grading for routine oncology digital pathology applications.

Duration: 01.10.2015 - 30.09.2018

MaDiPath investigates the research and establishment of mass spectrometric methods, in this case MALDI Imaging, for digital pathology. The aim of the project is to develop methods that enable an objective, reproducible and automated basis for pathological tumor diagnostics and the personalized course and therapy planning based on this.

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MALDI Imaging Lab – An interdisciplinary core facility for the acquisition and analysis of imaging mass spectrometry data

Duration: 01.07.2011 - 31.12.2018
PI: Peter Maaß

The MALDI Imaging Lab, MIL, is a core facility and research facility specialising in the acquisition of imaging mass spectrometric data. Both uni-internal and external interested parties can have their samples measured at the instrument centre. The services offered include sample preparation, measurement, possible post-treatments such as staining and microscopy, as well as computer-assisted evaluation of the data.

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HYPERMATH - Hyperspectral Imaging: Mathematical Methods for Innovations in Medicine and Industry

Duation: 01.07.2013 - 30.10.2016
PI: Peter Maaß

In HYPERMATH, data-adapted and application-specific approach functions for efficient data evaluation and approximations are determined. In addition, inherent localisation problems of the underlying measurement methods are mathematically captured and analysed. The procedures based on this take multi-scale structures into account in order to be able to efficiently process data sets with one trillion and more values.

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Entwicklung eines Digital-Staining-Verfahrens als pathologisch-histologisches Diagnosewerkzeug auf Basis der MALDI-Imaging-Technologie

Duration: 01.07.2014 - 30.06.2016
PI: Peter Maaß

The project focuses on the development of novel mathematical methods for the evaluation of MALDI imaging spectra and the creation of Standard Operating Procedures (SOP) for sample preparation and data acquisition. These developments are exemplified by tumours from the pancreas and the lung as well as metastases from the liver and are thus directly related to important questions in oncology.

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SceneNet - Mobile Crowd Sourcing Video Scene Reconstruction

Duration: 01.02.2013 - 30.01.2016
PI: Peter Maaß

For some years now, concerts, sporting events or family celebrations can hardly do without filming the scenes with smartphones. These videos show only a small angle of the scenario and are often of low quality. The SceneNet project aimed to transfer audio-visual recordings of a public event into a video sequence of the highest quality. In this video, an event can then be viewed interactively from a wide variety of angles.


MALDI AMK - 3D MALDI imaging for analysis of proteomic markers and clinical drug distribution

Duration: 01.04.2011 - 30.07.2014
PI: Peter Maaß

In this project, clinical oncological questions are explored directly in organs and tissues which require the context of the highly complex, heterogeneous 3D tissue composite in close cooperation with medical partners. A particular challenge here is 3D visualisation and direct interaction with this 3D data.

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UNLocX - Uncertainty principles versus localization properties, function systems for efficient coding schemes

Duration: 01.09.2010 - 30.08.2013
PI: Peter Maaß

A new generation of signal processing algorithms is to be tested, which - for example in medical image processing - will make it possible to tackle problems whose complexity was previously too high and, in addition, enable even more efficient compression and data transmission.

Fliege SPP1324

SPP 1324 - Adaptive Wavelet Frame Methods for Operator Equations: Sparse Grids, Vector-Valued Spaces, and Applications to Nonlinear Inverse Parabolic Problems

Duration: 01.04.2009 - 01.12.2013
PI: Peter Maaß

The realization that the embryogenesis of organisms is controlled by genes represents a milestone in modern biological research. This gave rise to the interest in understanding the processes involved quantitatively and, if possible, modeling them. This challenge is taken up by the cooperation project of the Center for Industrial Mathematics (ZeTeM) with the University of Marburg within the DFG priority program SPP 1324. Specifically, it is about the solution of an ill-posed, nonlinear operator equation Ax=y, which maps differentiably between Banach spaces.


Spatially three-dimensionally resolved metabolic analysis for medicine

Duration: 01.07.2010 - 30.06.2012
PI: Peter Maaß

In this project, technical process chains will be worked out to develop a 3D imaging method. This will enable the protein spectrum of an entire organ or disease-related lesion to be captured and analysed in its full complexity. This includes the distribution and metabolisation of active substances in the pathologically altered tissues (e.g. tumours) and the directly related therapy response.