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International MICCAI Brainlesion Workshop

BrainLes 2018: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries pp 352–363Cite as

Ischemic Stroke Lesion Segmentation in CT Perfusion Scans Using Pyramid Pooling and Focal Loss

Part of the Lecture Notes in Computer Science book series (LNIP,volume 11383)

Abstract

We present a fully convolutional neural network for segmenting ischemic stroke lesions in CT perfusion images for the ISLES 2018 challenge. Treatment of stroke is time sensitive and current standards for lesion identification require manual segmentation, a time consuming and challenging process. Automatic segmentation methods present the possibility of accurately identifying lesions and improving treatment planning. Our model is based on the PSPNet, a network architecture that makes use of pyramid pooling to provide global and local contextual information. To learn the varying shapes of the lesions, we train our network using focal loss, a loss function designed for the network to focus on learning the more difficult samples. We compare our model to networks trained using the U-Net and V-Net architectures. Our approach demonstrates effective performance in lesion segmentation and ranked among the top performers at the challenge conclusion.

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Authors and Affiliations

  1. Computer Science and Artificial Intelligence Lab, MIT, Cambridge, MA, USA

    S. Mazdak Abulnaga

  2. Philips Research North America, Cambridge, MA, USA

    S. Mazdak Abulnaga & Jonathan Rubin

Authors
  1. S. Mazdak Abulnaga
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  2. Jonathan Rubin
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Corresponding author

Correspondence to S. Mazdak Abulnaga .

Editor information

Editors and Affiliations

  1. University Hospital of Zurich, Zürich, Switzerland

    Alessandro Crimi

  2. University of Pennsylvania, Philadelphia, PA, USA

    Spyridon Bakas

  3. University Medical Center Utrecht, Utrecht, The Netherlands

    Hugo Kuijf

  4. National Cancer Institute, Bethesda, MD, USA

    Farahani Keyvan

  5. University of Bern, Bern, Switzerland

    Mauricio Reyes

  6. Erasmus University Medical Center, Rotterdam, The Netherlands

    Theo van Walsum

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Abulnaga, S.M., Rubin, J. (2019). Ischemic Stroke Lesion Segmentation in CT Perfusion Scans Using Pyramid Pooling and Focal Loss. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2018. Lecture Notes in Computer Science(), vol 11383. Springer, Cham. https://doi.org/10.1007/978-3-030-11723-8_36

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  • DOI: https://doi.org/10.1007/978-3-030-11723-8_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11722-1

  • Online ISBN: 978-3-030-11723-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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