Front Cover: Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation (Small Methods 7/2021). Issue 7 (14th July 2021)

• Record Type: Journal Article
• Authors: Mill, Leonid; Wolff, David; Gerrits, Nele; Philipp, Patrick; Kling, Lasse; Vollnhals, Florian; Ignatenko, Andrew; Jaremenko, Christian; Huang, Yixing; De Castro, Olivier; Audinot, Jean‐Nicolas; Nelissen, Inge; Wirtz, Tom; Maier, Andreas; Christiansen, Silke
• Is Part Of: Small methods. Volume 5:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-07-14
• Subjects: helium ion microscopy -- image analysis -- machine learning -- nanoparticles -- segmentation -- toxicology; Nanotechnology -- Methodology -- Periodicals; Nanotechnology -- Periodicals; Periodicals; 620.5028
• DOI: 10.1002/smtd.202170028
• Languages: English
• ISSNs: 2366-9608

Abstract

Abstract : In article number 2100223, Mill and co‐workers demonstrated a novel methodology that tackles the data annotation problem for the deep learning‐based segmentation of complex nanoparticle agglomerates in helium ion microscopy images. The study paves the way toward automated and high‐throughput nanoparticle image analysis for a variety of applications.