An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training

Author:

Ravi DanieleORCID,Barkhof FrederikORCID,Alexander Daniel C.,Puglisi LemuelORCID,Parker Geoffrey J.M.ORCID,Eshaghi ArmanORCID

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference49 articles.

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4. SteGANomaly: Inhibiting CycleGAN steganography for unsupervised anomaly detection in brain MRI;Baur,2020

5. Fully convolutional network for liver segmentation and lesions detection;Ben-Cohen,2016

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