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). 

• Research Areas
  

  • Pattern Recognition & Machine Learning

    

    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.

    Medical Image Processing

    

    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.

    Big Data Applications

    

    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.

  Available Theses
  

  Extension of an audio-recordings database with features for similarity search (Master Arbeit) Betreuer: Maier, Andreas; Meyer-Wegener, Klaus

  Image Analysis for Microscopical Layer Characterization and Morphological Feature Parametrization (Master Arbeit) Betreuer: Maier, Andreas; Steidl, Stefan; Spies, Ines

  Recent Publications
  

  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

  Lu, Yanye; Kowarschik, Markus; Huang, Xiaolin; Xia, Yan; Choi, Jang‐Hwan; Chen, Shuqing; Hu, Shiyang; Ren, Qiushi; Fahrig, Rebecca; Hornegger, Joachim; Maier, Andreas: A learning-based material decomposition pipeline for multi-energy x-ray imaging In: Medical Physics

  Mirzaalian Dastjerdi, Houman; Töpfer, Dominique; Rupitsch, Stefan; Maier, Andreas: Measuring Surface Area of Skin Lesions with 2D and 3D Algorithms In: International Journal of Biomedical Imaging

  Seewald, Lucas Adams; Rodrigues, Vinicius Facco; Ollenschläger, Malte; Stoffel Antunes, Rodolfo; da Costa, Cristiano Andre; sa Rosa Righi, Rodrigo; de Silveira, Luiz Gonzaga; Maier, Andreas; Eskofier, Björn; Fahrig, Rebecca: Toward analyzing mutual interference on infrared-enabled depth cameras In: Copmuter Vision and Image Understanding

  Bayer, Siming; Wydra, Adrian; Zhong, Xia; Ravikumar, Nishant; Strumia, Maddalena; Schaffert, Roman; Ostermeier, Martin; Fahrig, Rebecca; Maier, Andreas: An anthropomorphic deformable phantom for brain shift simulation In: IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

  Kurzendorfer, Tanja: Fully Automatic Segmentation of Anatomy and Scar from LGE-MRI In:

  Lu, Yanye; Kowarschik, Markus; Huang, Xiaolin; Chen, Shuqing; Ren, Qiushi; Fahrig, Rebecca; Hornegger, Joachim; Maier, Andreas: Material Decomposition Using Ensemble Learning for Spectral X-ray Imaging In: IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES

  Husvogt, Lennart; Arya, Malvika; Alibhai, A. Yasin; Moult, Eric; Duker, Jay S.; Waheed, Nadia K.; Fujimoto, James G.; Maier, Andreas: Automatic detection of capillary dilation and looping in patients with diabetic retinopathy from optical coherence tomography angiography data In: ARVO Annual Meeting 2018

  Bayer, Siming; Wydra, Adrian; Zhong, Xia; Ravikumar, Nishant; Strumia, Maddalena; Schaffert, Roman; Ostermeier, Martin; Fahrig, Rebecca; Maier, Andreas: An anthropomorphic deformable phantom for brain shift simulation In: IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

  Meister, Felix; Passerini, Tiziano; Mihalef, Viorel; Tuysuzoglu, Ahmet; Maier, Andreas; Mansi, Tommaso: Towards Fast Biomechanical Modeling of Soft Tissue Using Neural Networks In: Medical Imaging Meets NeurIPS
• Cooperations
  

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  LME-News
  

  Meldungen und Termine

  Sieben Nachwuchswissenschaftler der Universität Erlangen-Nürnberg werden an der diesjährigen Tagung der Nobelpreisträger in Lindau teilnehmen. Sie gehören damit zu den 560 jungen Forschern, die zwischen dem 1. und dem 6. Juli...[more]

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  Respons - Regional Sponsorship

  Neue Wege des regionalen Networkinghttp://www.respons.org/flyer.pdf   Weitere InformationenProf. Dr.-Ing. Joachim HorneggerTel.: 09131 85-27775E-Mail: Joachim.Hornegger(at)informatik.uni-erlangen.de  [more]

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  Tag der Informatik

  Stefan Wenhardt vom Lehrstuhl für Mustererkennung hält einen Vortrag zu diesem Projekt. Er stellt kurz die verschiedenen Ligen des Robocups vor, wie z.B. Small Size League, in der unser Team ER-Force angetreten ist. Ebenso werden...[more]

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  Auszeichnungen

  Beim Workshop "Bildverarbeitung für die Medizin" im März 2007 in München gingen Auszeichnungen für herausragende Arbeiten in allen drei Preiskategorien an den Erlanger Lehrstuhl für Mustererkennung. Der zweite Platz bei...[more]

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  Bessere Therapien für Kinder mit Lippen-Kiefer-Gaumen-Spalten

  Eines der Markenzeichen der Universität Erlangen-Nürnberg ist die enge Zusammenarbeit zwischen Medizin und Technik. Diese erfolgreiche Verbindung wird nun in einem neuen Projekt zur automatischen Bewertung von Sprechstörungen von...[more]

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  Computer analysiert Sprechstörungen

  Eines der Markenzeichen der Universität Erlangen-Nürnberg ist die enge Zusammenarbeit zwischen Medizin und Technik. Diese erfolgreiche Verbindung wird nun in einem neuen Projekt zur automatischen Bewertung von Sprechstörungen von...[more]

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