APSIPA Transactions on Signal and Information Processing > Vol 14 > Issue 5

LG-NuSegHop: A Local-to-global Self-supervised Pipeline for Nuclei Instance Segmentation

Vasileios Magoulianitis, University of Southern California, USA, magoulia@usc.edu , Catherine A. Alexander, University of Southern California, USA, Jiaxin Yang, University of Southern California, USA, C.-C. Jay Kuo, University of Southern California, USA
 
Suggested Citation
Vasileios Magoulianitis, Catherine A. Alexander, Jiaxin Yang and C.-C. Jay Kuo (2025), "LG-NuSegHop: A Local-to-global Self-supervised Pipeline for Nuclei Instance Segmentation", APSIPA Transactions on Signal and Information Processing: Vol. 14: No. 5, e402. http://dx.doi.org/10.1561/116.20250057

Forthcoming: 18 Dec 2025
© 2025 V. Magoulianitis, C. A. Alexander, J. Yang and C.-C. J. Kuo
 
Subjects
Medical image analysis,  Statistical/Machine learning,  Biological and biomedical signal processing
 
Keywords
Histopathology imagesnucleus segmentationself-supervisiondata-driven feature extraction
 

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This is published under the terms of CC BY-NC.

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In this article:
Introduction 
Related Work 
Materials and Methods 
Experimental Results 
Conclusion 
References 

Abstract

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DOI:10.1561/116.20250057

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APSIPA Transactions on Signal and Information Processing Special Issue - AI for Medical Image Analysis
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