Pingfan Song — accepted AI-conference papers

2021

Model-Inspired Deep Learning for Light-Field Microscopy with Application to Neuron Localization

Pingfan Song, Herman Verinaz-Jadan, Carmel L. Howe, Peter Quicke, Amanda J. Foust, Pier Luigi Dragotti

ICASSP 2021accepted

Light-field microscopes are able to capture spatial and angular information of incident light rays. This allows reconstructing 3D locations of neurons from a single snap-shot. In this work, we propose a model-inspired deep learning approach to perform fast and robust 3D localization of sources using…

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2020

Volume Reconstruction for Light Field Microscopy

Herman Verinaz-Jadan, Pingfan Song, Carmel L. Howe, Amanda J. Foust, Pier Luigi Dragotti

ICASSP 2020accepted

Light Field Microscopy (LFM) is a 3D imaging technique that captures volumetric information in a single snapshot. It is appealing in microscopy because of its simple implementation and the peculiarity that it is much faster than methods involving scanning. However, volume reconstruction for LFM suff…

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2019

Magnetic Resonance Fingerprinting Using a Residual Convolutional Neural Network

Pingfan Song, Yonina C. Eldar, Gal Mazor, Miguel R. D. Rodrigues

ICASSP 2019accepted

Conventional dictionary matching based MR Fingerprinting (MRF) reconstruction approaches suffer from time-consuming operations that map temporal MRF signals to quantitative tissue parameters. In this paper, we design a 1-D residual convolutional neural network to perform the signature-to-parameter m…

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