Work

Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-supervised Segmentation

Year: 2022

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-031-16443-9_56

Authors: Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Yipeng Hu, Joseph Jacob

Institutions: University College London, GlaxoSmithKline (United Kingdom), GlaxoSmithKline Research & Development Limited (United Kingdom)

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: GlaxoSmithKline, Wellcome Trust, UK Research and Innovation, National Institute for Health and Care Research, University College London Hospitals NHS Foundation Trust, Engineering and Physical Sciences Research Council, UCL Engineering, University College London

Awards: G2810537366, G339059223, G4353029269, G4669776581, G5433652116, G5619513383, G6127694706, G6367307199, G844244329, G8807293646, G8849905504

OpenAlex ID: W4296122736

FWCI: 1.088

Cites: 19

Cited by: 12

Related to: 10