Friedrich-Alexander-Universität Erlangen
Lehrstuhl für Mustererkennung
Martensstraße 3
91058 Erlangen
Pattern Recognition deals with the automatic classification and analysis of sensor input data. In this area we have work groups in 
Speech Recognition and Understanding, Computer Vision, Multiple Criteria Optimization, Image Analysis, Image Segmentation, and Image Fusion.
The research area medical image processing investigates formation and analysis of images in medicine. Currently the groups Analytic Reconstruction and Consistency, Computed Tomography: Algebraic Reconstruction and Motion, Magnetic Resonance Imaging, Phase-Contrast Imaging, and Ophthalmic Imaging are working on such topics.
With the sheer amount of "big data", new opportunities are available also for pattern recognition and machine learning. Examples are deep learning and 
precision learning. In this area, we have the groups of Learning Approaches for Medical Big Data Analysis, Population Modelling, and Enterprise Computing.
Pattern Recognition deals with the automatic classification and analysis of sensor input data. In this area we have work groups in Speech Recognition and Understanding, Computer Vision, Multiple Criteria Optimization, Image Analysis, Image Segmentation, and Image Fusion.
The research area medical image processing investigates formation and analysis of images in medicine. Currently the groups Analytic Reconstruction and Consistency, Computed Tomography: Algebraic Reconstruction and Motion, Magnetic Resonance Imaging, Phase-Contrast Imaging, and Ophthalmic Imaging are working on such topics.
With the sheer amount of "big data", new opportunities are available also for pattern recognition and machine learning. Examples are deep learning and precision learning. In this area, we have the groups of Learning Approaches for Medical Big Data Analysis, Population Modelling, and Enterprise Computing.
Researchers and students at Pattern Recognition Lab (LME) work on the development and implementation of algorithms to classify and analyze patterns like images or speech. The research is mostly interdisciplinary and is focussed on medical- and health engineering. The LME has close national and international collaborations with other universities, research institutes and industrial partners.
A summary of the projects at the Pattern Recognition Lab is available for download as a comprehensive brochure (PDF).
Franziska Schirrmacher, a former PhD student at the Pattern Recognition Lab, receives this year's Luise Prell-Preis for her excellent Master's thesis, from which publications evolved. Parts of the thesis are published in a MICCAI...[more]
On next Monday, Prof. Michael King from the University of Massachusetts Medical School will give a talk in our lab. Title: "Respiratory Motion Correction Methods for Cardiac SPECT and DL Denoising”Time: 15:00 on...[more]
Sulaiman Vesal, PhD student at the Pattern Recognition Lab, was awarded the second best work in the STACOM Multi-sequence Cardiac MR Segmentation Challenge at MICCAI 2019. The award was given for the paper: "Automated...[more]
Congratulations to Maniraman Periyasamy, Meike Biendl and Alexander Richter, Jonas Utz, and Henrik Willer for their outstanding achievements in the Deep Learning Challenge 2019! A great success. Please...[more]
In a cooperation with Marc Kachelriess (DKFZ), Michael Lell (Klinikum Nürnberg Nord) and our lab, we successfully applied for another DFG Project. The aim of the project is to estimate patient-individualised dose for a CT scan...[more]
Camilo Vasquez, a PhD student of our lab was warded with the best paper award at the Iberoamerican conference on pattern recognition (CIARP 2019) that was held in Havana (Cuba) from 28.10.2019 to 31.10.2019. The award was given...[more]
Extension of an audio-recordings database with features for similarity search (Master Arbeit) Betreuer: Maier, Andreas; Meyer-Wegener, Klaus
Choi, Jang-hwan; McWalter, Emily; Datta, Sanjit; Müller, Kerstin; Maier, Andreas; Gold, Garry; Levenston, Marc; Fahrig, Rebecca: In Vivo 3D Measurement of Time-dependent Human Knee Joint Compression and Cartilage Strain During Static Weight-Bearing In: ORS 2016 Annual Meeting
Pattern Recognition deals with the automatic classification and analysis of sensor input data. In this area we have work groups in Speech Recognition and Understanding, Computer Vision, Multiple Criteria Optimization, Image Analysis, Image Segmentation, and Image Fusion.
The research area medical image processing investigates formation and analysis of images in medicine. Currently the groups Analytic Reconstruction and Consistency, Computed Tomography: Algebraic Reconstruction and Motion, Magnetic Resonance Imaging, Phase-Contrast Imaging, and Ophthalmic Imaging are working on such topics.
With the sheer amount of "big data", new opportunities are available also for pattern recognition and machine learning. Examples are deep learning and precision learning. In this area, we have the groups of Learning Approaches for Medical Big Data Analysis, Population Modelling, and Enterprise Computing.
Extension of an audio-recordings database with features for similarity search (Master Arbeit) Betreuer: Maier, Andreas; Meyer-Wegener, Klaus
Choi, Jang-hwan; McWalter, Emily; Datta, Sanjit; Müller, Kerstin; Maier, Andreas; Gold, Garry; Levenston, Marc; Fahrig, Rebecca: In Vivo 3D Measurement of Time-dependent Human Knee Joint Compression and Cartilage Strain During Static Weight-Bearing In: ORS 2016 Annual Meeting
It is a great pleasure to announce that Elisabeth Hoppe has been selected to the final six best AI Researchers in Germany under 30 years. There is a public vote that will determine the winner. Please give her your vote...[more]
Also this year, the Pattern Recognition Lab and its alumni were very successful at MICCAI 2019. Congratulations to Bastian Bier and Mathias Unberath for winning the IJCARS MICCAI 2018 Best Paper Award for their contribution...[more]
Meta-learning has recently yielded state-of-the-art results in few-shot learning. However, current algorithm implementations are deeply tied to the datasets they were developed on.As a consequence researchers often reimplement...[more]
This week is international open access week. As a representative for Germany, Daniel Stromer shared his ideas at Springer Nature and talks about the benefits of OA in translational research, his projects, and...[more]
Aline Sindel, PhD student at the Pattern Recognition Lab received with her Master Thesis "Learning-based Image Super-Resolution for 3-D Magnetic Resonance Imaging" the second prize at the “Informatik in den...[more]
Following the invitation by Prof. Dr. Nabavi (head of Department of Neurosurgery in KRH Nordstadt Klinikum Hannover) , our PhD candidates Siming Bayer, Alexander Preuhs and Stephan Seitz visited the Department of Neurosurgery in...[more]
Tired of doing research? Need a break? Need some good bavarian coffee? Check out the Bavarian Roasting Company and become a fan on Facebook.
