New publication on fully automated quantification of prostate elasticity

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Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation
Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation

Our @team_dewey group member Nader Aldoj just submitted his work to #arxiv by the Cornell University. This research has been done with the help of our colleagues Federico, Anja, Patrick and Ingolf and funded by @dfg_public. 

Abstract:

Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using trained network-based image segmentation, we investigated if MRE data suffice to extract anatomical and viscoelastic information for automatic tabulation of zonal mechanical properties of the prostate. Overall, 40 patients with benign prostatic hyperplasia (BPH) or prostate cancer (PCa) were examined with three magnetic resonance imaging (MRI) sequences: T2-weighted MRI (T2w), diffusion-weighted imaging (DWI), and MRE-based tomoelastography yielding six independent sets of imaging data per patient (T2w, DWI, apparent diffusion coefficient (ADC), MRE magnitude, shear wave speed, and loss angle maps).

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Nader Aldoj