A Self-Adaptive Network for Multiple Sclerosis Lesion Segmentation From Multi-Contrast MRI With Various Imaging Sequences

  title={A Self-Adaptive Network for Multiple Sclerosis Lesion Segmentation From Multi-Contrast MRI With Various Imaging Sequences},
  author={Yushan Feng and Huitong Pan and Craig H. Meyer and Xue Feng},
  journal={2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)},
  • Yushan Feng, Huitong Pan, Xue Feng
  • Published 19 November 2018
  • Computer Science
  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
Deep neural networks have shown promises in the lesion segmentation of multiple sclerosis (MS) from multi-contrast MRI including T1, T2, PD and FLAIR sequences. However, one challenge in deploying such networks into clinical practice is missing MRI sequences due to the variability of image acquisition protocols. Therefore, trained networks need to adapt to practical situations where specific MRI sequences are unavailable. In this paper, we propose a DNN-based MS lesion segmentation framework… 

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