Deep learning-driven macroscopic AI segmentation model for brain tumor detection via digital pathology: Foundations for terahertz imaging-based AI diagnostics

Deep learning-driven macroscopic AI segmentation model for brain tumor detection via digital pathology: Foundations for terahertz imaging-based AI diagnostics

We used deep learning methods to develop an AI model capable of autonomously delineating cancerous regions in digital pathology images (H&E-stained images). By using a transgenic brain tumor model derived from the TS13-64 brain tumor cell line, we digitized a total of 187 H&E-stained images...

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Bibliographic Details
Main Authors: Myeong Suk Yim, Yun Heung Kim, Hyeon Sang Bark, Seung Jae Oh, Inhee Maeng, Jin-Kyoung Shim, Jong Hee Chang, Seok-Gu Kang, Byeong Cheol Yoo, Jae Gwang Kwon, Jungsup Byun, Woon-Ha Yeo, Seung-Hwan Jung, Han-Cheol Ryu, Se Hoon Kim, Hyun Ju Choi, Young Bin Ji
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Heliyon
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024164833
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