561-04-014 ISMRM Abstract

Impact of highly accelerated deep learning reconstruction on common brain segmentation software pipelines

Primary: Acquisition & Reconstruction - Image Reconstruction: AI

Secondary: Analysis Methods - Data Processing

561-04-014 · Deep Learning Meets k-Space: New Frontiers in Reconstruction · Wednesday, 13 May, 2:35 PM–3:30 PM · Digital Posters Row B

Keywords: Brain Deep learning reconstruction Image Quality Metrics

Accepted

Kain A Kyle ¹, Taylor Emsden², Daniel Cornfeld^2,3, Paul M Condron^2,3, Sergio Dempsey⁴

¹GE HealthCare (Sydney, AUS), Sydney, Australia

²Mātai Medical Research Institute, Gisborne, New Zealand

³University of Auckland, Auckland, New Zealand

⁴GE HealthCare, Gisborne, New Zealand

Presenting Author: Kain A Kyle

Synopsis

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References

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8. Isensee F, Schell M, Pflueger I, et al. Automated brain extraction of multisequence MRI using artificial neural networks. Hum Brain Mapp. 2019;40(17):4952-4964. doi:10.1002/hbm.24750 [doi]

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http://echo.ismrm.org/p/ISMRM2026/561-04-014