Deriving brain imaging biomarkers with deep learning

Ö. Smedby

doi:10.1117/12.2593648

2 September 2021 Deriving brain imaging biomarkers with deep learning

Ö. Smedby

Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 118040Q (2021) https://doi.org/10.1117/12.2593648
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States

Abstract

A central research topic in medical image processing is the development of imaging biomarkers, i.e. image-based numeric measures of the degree (or probability) of disease. Typically, they rely on segmentation of an anatomical or pathological structure in a radiological image, followed by quantitative measurement. With much of traditional image processing methods being supplanted by machine learning techniques, the identification of new imaging biomarkers is also often made with such techniques, in particular deep learning. Successful examples include quantitative assessment of Alzheimer’s disease and Parkinson’s disease based on brain MRI data, as well as image-based brain age estimation.

Conference Presentation

Citation Download Citation

Ö. Smedby "Deriving brain imaging biomarkers with deep learning", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 118040Q (2 September 2021); https://doi.org/10.1117/12.2593648

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