Histopathology image classification: Highlighting the gap between manual analysis and AI automation

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Summary

Description	Figure 2. First row represents Adipose (ADI), background (BACK), debris (DEB), lymphocytes (LYM), mucus (MUC), smooth muscle (MUS), normal colonic mucosa (NORM), cancer-associated stroma (STR), and colorectal adenocarcinoma epithelium (TUM). The second row data set was obtained by applying normalization to the same tissue examples in the first row.
Source	Doğan, Refika S.; Yılmaz, Bülent (2024). "Histopathology image classification: Highlighting the gap between manual analysis and AI automation". Frontiers in Oncology 13: 1325271. doi:10.3389/fonc.2023.1325271.
Date	2024
Author	Doğan, Refika S.; Yılmaz, Bülent
Permission (Reusing this file)	Creative Commons Attribution 4.0 International
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current	20:58, 20 May 2024		1,772 × 622 (313 KB)	Shawndouglas (talk \| contribs)

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Unique ID of original document	09E75C3197C38268CCB1E7B7041C3566
Software used	Adobe Photoshop CC 2015 (Windows)