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
  

  LME Alumnus to join Johns Hopkins Faculty

  

  It is a pleasure to announce that our recent alumnus, Mathias Unberath, has been appointed as Assistant Research Professor in the Department of Computer Science at Johns Hopkins University. His research focuses on novel...[more]

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  Papal Charters Project in the News

  Our papal charter project was the focus of a recently published article from the weekend magazine of the NN/NZ (1.9.18), for which Klaus Herbers (Medieval History Lab, FAU) and Vincent Christlein (PRL) were interviewed.   It...[more]

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  LME Success at STACOM Atrial Segmentation Challenge

  

  Sulaiman Vesal, PhD student at the Pattern Recognition Lab made second place in the STACOM left atrial segmentation challenge at MICCAI 2018. The participants were required to produce a computational framework capable of...[more]

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  MICCAI Young Scientist Award

  

  Bastian Bier, PhD Student at our lab, in collaboration with Mathias Unberath of the Johns Hopkins University were awarded the prestigious 2018 MICCAI Young Scientist Award for their contribution titled "X-ray-transform...[more]

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  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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