Search Results - "Lindner, Lydia"

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  1. 1

    Using Synthetic Training Data for Deep Learning-Based GBM Segmentation by Lindner, Lydia, Narnhofer, Dominik, Weber, Maximilian, Gsaxner, Christina, Kolodziej, Malgorzata, Egger, Jan

    “…In this work, fully automatic binary segmentation of GBMs (glioblastoma multiforme) in 2D magnetic resonance images is presented using a convolutional neural…”
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    Conference Proceeding Journal Article
  2. 2

    Lightweight Video Denoising using Aggregated Shifted Window Attention by Lindner, Lydia, Effland, Alexander, Ilic, Filip, Pock, Thomas, Kobler, Erich

    “…Video denoising is a fundamental problem in numerous computer vision applications. State-of-the-art attention-based denoising methods typically yield good…”
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    Conference Proceeding
  3. 3

    Fully Convolutional Mandible Segmentation on a valid Ground- Truth Dataset by Egger, Jan, Pfarrkirchner, Birgit, Gsaxner, Christina, Lindner, Lydia, Schmalstieg, Dieter, Wallner, Jurgen

    “…This contribution presents the automatic segmentation of the lower jawbone (mandible) in humans' computed tomography (CT) images with the support of trained…”
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    Conference Proceeding Journal Article
  4. 4

    Combining frequency and time-domain EEG features for classification of self-paced reach-and-grasp actions by Schwarz, Andreas, Pereira, Joana, Lindner, Lydia, Muller-Putz, Gernot R.

    “…Brain-computer interfaces (BCIs) might provide an intuitive way for severely motor impaired persons to operate assistive devices to perform daily life…”
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    Conference Proceeding Journal Article
  5. 5

    PET-Train: Automatic Ground Truth Generation from PET Acquisitions for Urinary Bladder Segmentation in CT Images using Deep Learning by Gsaxner, Christina, Pfarrkirchner, Birgit, Lindner, Lydia, Pepe, Antonio, Roth, Peter M., Egger, Jan, Wallner, Jurgen

    “…In this contribution, we propose an automatic ground truth generation approach that utilizes Positron Emission Tomography (PET) acquisitions to train neural…”
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    Conference Proceeding