Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification

Xin He, Guohao Ying, Jiyong Zhang*, Xiaowen Chu*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

The COVID-19 pandemic has threatened global health. Many studies have applied deep convolutional neural networks (CNN) to recognize COVID-19 based on chest 3D computed tomography (CT). Recent works show that no model generalizes well across CT datasets from different countries, and manually designing models for specific datasets requires expertise; thus, neural architecture search (NAS) that aims to search models automatically has become an attractive solution. To reduce the search cost on large 3D CT datasets, most NAS-based works use the weight-sharing (WS) strategy to make all models share weights within a supernet; however, WS inevitably incurs search instability, leading to inaccurate model estimation. In this work, we propose an efficient Evolutionary Multi-objective ARchitecture Search (EMARS) framework. We propose a new objective, namely potential, which can help exploit promising models to indirectly reduce the number of models involved in weights training, thus alleviating search instability. We demonstrate that under objectives of accuracy and potential, EMARS can balance exploitation and exploration, i.e., reducing search time and finding better models. Our searched models are small and perform better than prior works on three public COVID-19 3D CT datasets.
Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2022
Subtitle of host publication25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part I
EditorsLinwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li
PublisherSpringer Cham
Pages560–570
Number of pages11
Edition1st
ISBN (Electronic)9783031164316
ISBN (Print)9783031164309
DOIs
Publication statusPublished - 15 Sep 2022
Event25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022 - , Singapore
Duration: 18 Sep 202222 Sep 2022
https://link.springer.com/book/10.1007/978-3-031-16431-6 (Conference proceedings)

Publication series

NameLecture Notes in Computer Science
Volume13431
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameMICCAI: International Conference on Medical Image Computing and Computer-Assisted Intervention

Conference

Conference25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022
Country/TerritorySingapore
Period18/09/2222/09/22
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • 3D Computed Tomograph (CT)
  • COVID-19
  • Evolutionary Algorithm (EA)
  • Neural Architecture Search (NAS)
  • Weight-sharing

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