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
  

  Elisabeth Hoppe nominated as one of the top AI Researchers in Germany under 30!

  

  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]

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  Several Awards to Pattern Recognition Lab and its Alumni at MICCAI 2019

  

  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]

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  Best in Show award at the PyTorch Developer Conference for our library Torchmeta

  

  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]

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  International Open Access Week at Springer Nature: Daniel Stromer on publishing OA in Germany

  

  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]

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  PhD student receives ILW Award 2019

  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]

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  LME PhD candidates visit KRH Nordstadt Klinikum in Hannover

  

  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]

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