Automated Segmentation of Nucleus in Scattering-based Light Sheet Microscopy Images

Yongjun Kim; Jingwei Zhao; Ameer Nessaee; Eungjoo Lee; Brooke Liang; Michelle Khan; Eric Yang; Dongkyun Kang

Automated Segmentation of Nucleus in Scattering-based Light Sheet Microscopy Images

Yongjun Kim, Jingwei Zhao, Ameer Nessaee, Eungjoo Lee, Brooke Liang, Michelle Khan, Eric Yang, Dongkyun Kang

Research output: Contribution to conference › Paper › peer-review

Abstract

Scattering-based light sheet microscopy (sLSM) could visualize nucleus that are readily appreciable by pathologists. We developed an algorithm that automatically segments sLSM images for nucleus, which could be used for quantitative morphometric analysis.

Original language	English (US)
State	Published - 2024
Event	Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics - Fort Lauderdale, United States Duration: Apr 7 2024 → Apr 10 2024

Conference

Conference	Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics
Country/Territory	United States
City	Fort Lauderdale
Period	4/7/24 → 4/10/24

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Biomaterials
Biomedical Engineering
Atomic and Molecular Physics, and Optics

Cite this

Automated Segmentation of Nucleus in Scattering-based Light Sheet Microscopy Images. / Kim, Yongjun; Zhao, Jingwei; Nessaee, Ameer et al.
2024. Paper presented at Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics, Fort Lauderdale, United States.

Research output: Contribution to conference › Paper › peer-review

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title = "Automated Segmentation of Nucleus in Scattering-based Light Sheet Microscopy Images",

abstract = "Scattering-based light sheet microscopy (sLSM) could visualize nucleus that are readily appreciable by pathologists. We developed an algorithm that automatically segments sLSM images for nucleus, which could be used for quantitative morphometric analysis.",

author = "Yongjun Kim and Jingwei Zhao and Ameer Nessaee and Eungjoo Lee and Brooke Liang and Michelle Khan and Eric Yang and Dongkyun Kang",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s); Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics ; Conference date: 07-04-2024 Through 10-04-2024",

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T1 - Automated Segmentation of Nucleus in Scattering-based Light Sheet Microscopy Images

AU - Kim, Yongjun

AU - Zhao, Jingwei

AU - Nessaee, Ameer

AU - Lee, Eungjoo

AU - Liang, Brooke

AU - Khan, Michelle

AU - Yang, Eric

AU - Kang, Dongkyun

PY - 2024

Y1 - 2024

N2 - Scattering-based light sheet microscopy (sLSM) could visualize nucleus that are readily appreciable by pathologists. We developed an algorithm that automatically segments sLSM images for nucleus, which could be used for quantitative morphometric analysis.

AB - Scattering-based light sheet microscopy (sLSM) could visualize nucleus that are readily appreciable by pathologists. We developed an algorithm that automatically segments sLSM images for nucleus, which could be used for quantitative morphometric analysis.

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UR - http://www.scopus.com/inward/citedby.url?scp=85204909341&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85204909341

T2 - Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics

Y2 - 7 April 2024 through 10 April 2024

ER -

Automated Segmentation of Nucleus in Scattering-based Light Sheet Microscopy Images

Abstract

Conference

ASJC Scopus subject areas

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