UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Super-Focus: Domain Adaptation for Embryo Imaging via Self-supervised Focal Plane Regression

He, Chloe; Jacques, Celine; Chambost, Jerome; Malmsten, Jonas; Wouters, Koen; Freour, Thomas; Zaninovic, Nikica; ... Vasconcelos, Francisco; + view all (2022) Super-Focus: Domain Adaptation for Embryo Imaging via Self-supervised Focal Plane Regression. In: Wang, L and Dou, Q and Fletcher, PT and Speidel, S and Li, S, (eds.) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 25th International Conference. Proceedings, Part II. (pp. pp. 732-742). Springer: Cham, Switzerland. Green open access

[thumbnail of Super_resolution_MICCAI.pdf]
Preview
Text
Super_resolution_MICCAI.pdf - Accepted Version

Download (36MB) | Preview

Abstract

In recent years, the field of embryo imaging has seen an influx of work using machine learning. These works take advantage of large microscopy datasets collected by fertility clinics as routine practice through relatively standardised imaging setups. Nevertheless, systematic variations still exist between datasets and can harm the ability of machine learning models to perform well across different clinics. In this work, we present Super-Focus, a method for correcting systematic variations present in embryo focal stacks by artificially generating focal planes. We demonstrate that these artificially generated planes are realistic to human experts and that using Super-Focus as a pre-processing step improves the ability of a cell instance segmentation model to generalise across multiple clinics.

Type: Proceedings paper
Title: Super-Focus: Domain Adaptation for Embryo Imaging via Self-supervised Focal Plane Regression
Event: MICCAI 2022: 25th International Conference
ISBN-13: 978-3-031-16433-0
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-031-16434-7_70
Publisher version: https://doi.org/10.1007/978-3-031-16434-7_70
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Domain adaptation, Super-resolution, Embryology, Microscopy
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10158894
Downloads since deposit
0Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item