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Opportunities and Challenges for Deep Learning in Brain Lesions

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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (BrainLes 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 12962))

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Abstract

In recent years, deep learning techniques have shown potential for incorporation in many facets of the medical imaging pipeline, from image acquisition/reconstruction to segmentation/classification to outcome prediction. Specifically, these models can help improve the efficiency and accuracy of image interpretation and quantification. However, it is important to note the challenges of working with medical imaging data, and how this can affect the effectiveness of the algorithms when deployed. In this review, we first present an overview of the medical imaging pipeline and some of the areas where deep learning has been used to improve upon the current standard of care for brain lesions. We conclude with a section on some of the current challenges and hurdles facing neuroimaging researchers.

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Authors and Affiliations

  1. Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA

    Jay Patel, Ken Chang, Syed Rakin Ahmed, Ikbeom Jang & Jayashree Kalpathy-Cramer

  2. Massachusetts Institute of Technology, Cambridge, MA, USA

    Jay Patel & Ken Chang

  3. Harvard Graduate Program in Biophysics, Harvard Medical School, Harvard University, Cambridge, MA, USA

    Syed Rakin Ahmed

  4. Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, USA

    Syed Rakin Ahmed

  5. Department of Radiology, Harvard Medical School, Boston, MA, USA

    Ikbeom Jang & Jayashree Kalpathy-Cramer

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  1. Jay Patel
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  2. Ken Chang
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Correspondence to Jayashree Kalpathy-Cramer .

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Editors and Affiliations

  1. Sano Centre for Computational Personaliz, Kraków, Poland

    Alessandro Crimi

  2. University of Pennsylvania, Philadelphia, PA, USA

    Spyridon Bakas

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Patel, J., Chang, K., Ahmed, S.R., Jang, I., Kalpathy-Cramer, J. (2022). Opportunities and Challenges for Deep Learning in Brain Lesions. In: Crimi, A., Bakas, S. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2021. Lecture Notes in Computer Science, vol 12962. Springer, Cham. https://doi.org/10.1007/978-3-031-08999-2_2

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