Deep Neural Network-Based Classification of Spectrally Encoded Confocal Microscopy Images of Breast Cancer Tissue

Ameer Nessaee; Kivanc Kose; Elena F. Brachtel; Dongkyun Kang

Deep Neural Network-Based Classification of Spectrally Encoded Confocal Microscopy Images of Breast Cancer Tissue

Ameer Nessaee, Kivanc Kose, Elena F. Brachtel, Dongkyun Kang

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

Abstract

Spectrally Encoded Confocal Microscopy (SECM) previously demonstrated the ability to visualize cellular features of malignant breast tissues. In this paper, we developed a deep neural network-based method for automatically classifying SECM breast images.

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

Deep Neural Network-Based Classification of Spectrally Encoded Confocal Microscopy Images of Breast Cancer Tissue. / Nessaee, Ameer; Kose, Kivanc; Brachtel, Elena F. 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 = "Deep Neural Network-Based Classification of Spectrally Encoded Confocal Microscopy Images of Breast Cancer Tissue",

abstract = "Spectrally Encoded Confocal Microscopy (SECM) previously demonstrated the ability to visualize cellular features of malignant breast tissues. In this paper, we developed a deep neural network-based method for automatically classifying SECM breast images.",

author = "Ameer Nessaee and Kivanc Kose and Brachtel, {Elena F.} 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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language = "English (US)",

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T1 - Deep Neural Network-Based Classification of Spectrally Encoded Confocal Microscopy Images of Breast Cancer Tissue

AU - Nessaee, Ameer

AU - Kose, Kivanc

AU - Brachtel, Elena F.

AU - Kang, Dongkyun

PY - 2024

Y1 - 2024

N2 - Spectrally Encoded Confocal Microscopy (SECM) previously demonstrated the ability to visualize cellular features of malignant breast tissues. In this paper, we developed a deep neural network-based method for automatically classifying SECM breast images.

AB - Spectrally Encoded Confocal Microscopy (SECM) previously demonstrated the ability to visualize cellular features of malignant breast tissues. In this paper, we developed a deep neural network-based method for automatically classifying SECM breast images.

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M3 - Paper

AN - SCOPUS:85204917806

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

Y2 - 7 April 2024 through 10 April 2024

ER -

Deep Neural Network-Based Classification of Spectrally Encoded Confocal Microscopy Images of Breast Cancer Tissue

Abstract

Conference

ASJC Scopus subject areas

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