IIBI research team wins best machine-learning paper at ISBI 2019

L to R: Aniket Pramanik, Hermant Aggarwal and Mathews Jacob at ISBI 2019, Venice, Italy.

The Iowa Institute for Biomedical Imaging (IIBI) research team wins the best machine-learning paper at the International Symposium on Biomedical Imaging (ISBI 2019) in Venice, Italy. ISBI is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). 

The paper titled "Off-the-Grid Model Based Deep Learning (O-MoDL)," is authored by Aniket Pramanik, Hemant Aggarwal, and Mathews Jacob, who are researchers at the Computational Biomedical Imaging Group (CBIG) (https://research.engineering.uiowa.edu/cbig) within the Electrical and Computer Engineering and the Iowa Institute of Biomedical Imaging at the University of Iowa. The paper introduces a deep learning algorithm for the reconstruction of MRI data from highly under-sampled measurements, which facilitates significantly reducing the scan time of MRI scans. The model based deep learning strategy (MoDL) significantly reduces the training data demand compared to other deep learning image reconstruction schemes. Moreover, the off-the-grid strategy builds upon super-resolution image reconstruction algorithm, also developed at CBIG and won the best paper award at ISBI 2015. Aniket brings home a 32 GB NVIDIA Titan V CEO series card as the award. 

The IIBI and the University of Iowa will host next year's ISBI conference on April 4-8, 2020, at the Coralville Marriott Hotel and Conference Center (http://2020.biomedicalimaging.org/ ).  New to next year's meeting will be the addition of hands-on workshops held in IIBI in the Pappajohn Biomedical Discovery Building (PBDB).  Four-page paper submission opens on Thursday, August 1, 2019.  Paper submission deadline is Tuesday, October 15, 2019.

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