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

  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

  Breininger, Katharina; Hanika, Moritz; Weule, Mareike; Kowarschik, Markus; Pfister, Marcus; Maier, Andreas: Simultaneous reconstruction of multiple stiff wires from a single X-ray projection for endovascular aortic repair In: International Journal of Computer Assisted Radiology and Surgery

  Arbogast, Nikolaus; Kurzendorfer, Tanja; Breininger, Katharina; Mountney, Peter; Toth, Daniel; Narayan, Srinivas A.; Maier, Andreas: Workflow Phase Detection in Fluoroscopic Images Using Convolutional Neural Networks In: Workshop

  Mayr, Martin; Hoffmann, Mathis; Maier, Andreas; Christlein, Vincent: WEAKLY SUPERVISED SEGMENTATION OF CRACKS ON SOLAR CELLS USING NORMALIZED LP NORM In: 2019 IEEE International Conference on Image Processing (ICIP)

  Voigt, Ingmar; Mansi, Tommaso; Georgescu, Bogdan; Houle, Helene; Comaniciu, Dorin; Ene, Codruta; Scutaru, Mihai: Valve regurgitant detection for echocardiography In:

  Voigt, Ingmar; Mansi, Tommaso; Helene, Houle: Measurement Point Determination in Medical Diagnostic Imaging In:

  Camus, Estelle; Mansi, Tommaso; Voigt, Ingmar: Left Atrial Appendage Closure Guidance in Medical Imaging In:

  Scutaru, Mihai; Voigt, Ingmar; Mansi, Tommaso,; Ionasec, Razvan; Houle, Helene; Tatpati, Anand; Comaniciu, Dorin; Georgescu, Bogdan; El-Zehiri, Noha: Landmark detection with spatial and temporal constraints in medical imaging In:

  Henderson, Steve; Mansi, Tommaso; Tatpati, Anand; Voigt, Ingmar; Rao, Bimba: Continuously oriented enhanced ultrasound imaging of a sub-volume In:

  Tek, Huseyin; Georgescu, Bogdan; Mansi, Tommaso; Sauer, Frank; Comaniciu, Dorin; Houle, Helene; Voigt, Ingmar: Cardiac flow detection based on morphological modeling in medical diagnostic ultrasound imaging In:
• Cooperations
  

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  LME-News
  

  New research member

  Ronak Kosti started working with the Pattern Recognition Lab (PRL) as a Researcher for the EFI (Emerging Fields Initiative) funded project 'ICONOGRAPHICS'. This project focuses on computational understanding of paintings and...[more]

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  DFG grants funding for research on enhanced imaging in ophthalmology

  

  A key characteristic of research at the Pattern Recognition Lab is its embedding in multidisciplinary environments that ensure relevance and facilitate transfer to application. This paradigm is continued in a new project on...[more]

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  Best Poster Award at iCT 2019

  

  Deniz Neufeld, M.Sc. Student at our lab was awarded a Best Poster Award (2nd place) for her contribution titled "Realistic Image Synthesis of Imperfect Specimens using Generative Networks". Her work was done in...[more]

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  Award for Best Student Paper at BIOIMAGING/BIOSTEC

  

  Marc Aubreville, PhD student at the pattern recognition lab, was awarded the best student paper on this year's BIOIMAGING/BIOSTEC conference in Prague, Czech Republic. The paper, entitled "Field Of Interest Proposal for...[more]

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  Invited Talk by Natasha Elizabeth Morton

  On next Monday, Natasha Elizabeth Morton from ACRF Image X Institute from Sydney university will give a talk in our lab.   Titel: "Reducing imaging artefacts at the root of the cause: Respiratory Adaptive...[more]

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  New PhD student

  Prathmesh Madhu started working with the Pattern Recognition Lab as PhD researcher under Prof. Andreas Maier on the topic -"Scene understanding using deep learning" from December, 2018. He has a working experience of 2...[more]

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