Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction

Jo Schlemper, Jinming Duan, Cheng Ouyang, Chen Qin, Jose Caballero, Joseph V. Hajnal, Daniel Rueckert

Research output: Contribution to conferenceAbstractpeer-review

Abstract

We present simple reconstruction networks for multi-coil data by extending deep cascade of CNN's and exploiting the data consistency layer. In particular, we propose two variants, where one is inspired by POCSENSE and the other is calibration-less. We show that the proposed approaches are competitive relative to the state of the art both quantitatively and qualitatively.
Original languageEnglish
Publication statusSubmitted - 25 Sep 2019
EventISMRM 27th Annual Meeting & Exhibition, 11-16 May 2019 - alais des congrès de Montréal, 1001 Place Jean-Paul-Riopelle, Montreal, Canada
Duration: 11 May 201916 May 2019
https://www.ismrm.org/19m/

Conference

ConferenceISMRM 27th Annual Meeting & Exhibition, 11-16 May 2019
Country/TerritoryCanada
CityMontreal
Period11/05/1916/05/19
Internet address

Keywords

  • eess.IV
  • cs.CV
  • cs.LG
  • stat.ML

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