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
  

  LME Successful at MIT Hackathon

  

  Daniel Stromer and Lennart Husvogt, both PhD students at the Pattern Recognition Lab, were part of one the winning teams of the MIT Media Lab's CityRobotics Hackathon. The hackathon focused on the intersection of transportation,...[more]

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  PRL on title of local newspaper

  

  On Wednesday 29th of August our lab made it onto the title of the NZ with the European Time Machine Project. An Interview with more details is found on Page 20. Have fun reading the news![more]

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  "Medical Imaging Systems - An Introductory Guide" published

  

  It is a great pleasure to announce that our new text book "Medical Imaging Systems - An Introductory Guide“ has been published as open access version under this...[more]

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  Featured Story on Scale-Space Anisotropic Total Variation

  

  Our recently published paper "Scale-space Anisotropic Total Variation for Limited Angle Tomography" has been selected as one of the "featured stories" by the journal IEEE Transactions on Radiation and Plasma...[more]

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  Another NVIDIA GPU Grant Approved for PRL Member

  The NVIDIA Corporation donated a GPU to a member of the lab after she applied for the NVIDIA GPU Grant Program: https://developer.nvidia.com/academic_gpu_seeding Aline Sindel received a grant for her research on deep similarity...[more]

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  New Employee

  

  Alexandra Hauske joined the Pattern Recognition Lab on June 15th.   After training as a foreign language correspondent (in Spanish and English) at the Institut für Fremdsprachen und Auslandskunde at the...[more]

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