Implicit Neural Representations for Generative Modeling of Living Cell Shapes

David Wiesner, Julian Suk, Sven Dummer, David Svoboda, Jelmer M. Wolterink

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

5 Citations (Scopus)
67 Downloads (Pure)

Abstract

Methods allowing the synthesis of realistic cell shapes could help generate training data sets to improve cell tracking and segmentation in biomedical images. Deep generative models for cell shape synthesis require a light-weight and flexible representation of the cell shape. However, commonly used voxel-based representations are unsuitable for high-resolution shape synthesis, and polygon meshes have limitations when modeling topology changes such as cell growth or mitosis. In this work, we propose to use level sets of signed distance functions (SDFs) to represent cell shapes. We optimize a neural network as an implicit neural representation of the SDF value at any point in a 3D+time domain. The model is conditioned on a latent code, thus allowing the synthesis of new and unseen shape sequences. We validate our approach quantitatively and qualitatively on C. elegans cells that grow and divide, and lung cancer cells with growing complex filopodial protrusions. Our results show that shape descriptors of synthetic cells resemble those of real cells, and that our model is able to generate topologically plausible sequences of complex cell shapes in 3D+time.
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 IV
EditorsLinwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li
PublisherSpringer
Pages58-67
Number of pages10
ISBN (Electronic)978-3-031-16440-8
ISBN (Print)978-3-031-16439-2
DOIs
Publication statusPublished - 2022
Event25th International Conference on Medical Computing and Computer-Assisted Intervention, MICCAI 2022 - Resorts World Convention Centre Singapore, Singapore, Singapore
Duration: 18 Sept 202222 Sept 2022
Conference number: 25
https://conferences.miccai.org/2022/en/

Publication series

NameLecture Notes in Computer Science
Volume13434

Conference

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

Keywords

  • 22/4 OA procedure

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