Improved Counting and Localization From Density Maps for Object Detection in 2D and 3D Microscopy Imaging

Shijie Li, Guido Gerig, Thomas Ach

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Crowd object counting and localization are key steps for quantitative analysis in large-scale microscopy applications. Previous methods producing density maps based on deep learning have reached a high level of accuracy for object counting by assuming that object counting is equivalent to the integration of the density map. However, this model fails when objects overlap significantly and/or present fuzzy boundaries regarding accurate localization. To overcome this limitation, we propose an alternative method to count and localize objects from the density map. Our procedure includes the following three key aspects: 1) Proposing a new connected-component analysis method based on the statistical properties of the density map, 2) optimizing the counting results for those objects which are well-detected based on the proposed counting method, and 3) improving localization of poorly detected objects using the proposed counting method as prior information. Validation includes processing microscopy data with known ground truth and comparison with other models that use conventional processing of the density map. Our results show improved performance in counting and localization of objects in 2D and 3D microscopy data. Furthermore, the proposed method is generic, considering various applications that rely on the density map approach.

Original languageEnglish (US)
Title of host publication2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023
PublisherIEEE Computer Society
ISBN (Electronic)9781665473583
DOIs
StatePublished - 2023
Event20th IEEE International Symposium on Biomedical Imaging, ISBI 2023 - Cartagena, Colombia
Duration: Apr 18 2023Apr 21 2023

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2023-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference20th IEEE International Symposium on Biomedical Imaging, ISBI 2023
Country/TerritoryColombia
CityCartagena
Period4/18/234/21/23

Keywords

  • density map
  • object counting
  • object localization

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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