Comparative analysis of Ki-67 labeling index morphometry using deep learning, conventional image analysis, and manual counting

Comparative analysis of Ki-67 labeling index morphometry using deep learning, conventional image analysis, and manual counting

The Ki-67 labeling index is essential for predicting the prognosis of breast cancer and for diagnosing neuroendocrine and gastrointestinal stromal tumors. However, current manual counting and digital image analysis (DIA)-based methods are limited in terms of accurate estimation. This study aimed to...

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Bibliographic Details
Main Authors: Mohammad Rizwan Alam, Kyung Jin Seo, Kwangil Yim, Phoebe Liang, Joe Yeh, Chifu Chang, Yosep Chong
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Translational Oncology
Subjects:
Ki-67 antigen
Morphometry
Immunohistochemistry
Deep learning
Artificial intelligence
Digital image analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S1936523324002869
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http://www.sciencedirect.com/science/article/pii/S1936523324002869

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