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The utility of color normalization for <scp>AI</scp> ‐based diagnosis of hematoxylin and eosin‐stained pathology images
- Source :
- The Journal of Pathology. 256:15-24
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- The color variation of hematoxylin and eosin (HE)-stained tissues has presented a challenge for applications of artificial intelligence (AI) in digital pathology. Many color normalization algorithms have been developed in recent years in order to reduce the color variation between HE images. However, previous efforts in benchmarking these algorithms have produced conflicting results and none have sufficiently assessed the efficacy of the various color normalization methods for improving diagnostic performance of AI systems. In this study, we systematically investigated eight color normalization algorithms for AI-based classification of HE-stained histopathology slides, in the context of using images both from one center and from multiple centers. Our results show that color normalization does not consistently improve classification performance when both training and testing data are from a single center. However, using four multi-center datasets of two cancer types (ovarian and pleural) and objective functions, we show that color normalization can significantly improve the classification accuracy of images from external datasets (ovarian cancer: 0.25 AUC increase, p = 1.6 e-05; pleural cancer: 0.21 AUC increase, p = 1.4 e-10). Furthermore, we introduce a novel augmentation strategy by mixing color-normalized images using three easily accessible algorithms that consistently improves the diagnosis of test images from external centers, even when the individual normalization methods had varied results. We anticipate our study to be a starting point for reliable use of color normalization to improve AI-based, digital pathology-empowered diagnosis of cancers sourced from multiple centers. © 2021 The Pathological Society of Great Britain and Ireland. Published by John WileySons, Ltd.
- Subjects :
- Normalization (statistics)
medicine.medical_specialty
Staining and Labeling
Color normalization
business.industry
H&E stain
Digital pathology
United Kingdom
3. Good health
030218 nuclear medicine & medical imaging
Pathology and Forensic Medicine
03 medical and health sciences
0302 clinical medicine
Artificial Intelligence
Neoplasms
030220 oncology & carcinogenesis
Digital image analysis
Pleural Cancer
medicine
Eosine Yellowish-(YS)
Humans
Radiology
Hematoxylin
business
Algorithms
Subjects
Details
- ISSN :
- 10969896 and 00223417
- Volume :
- 256
- Database :
- OpenAIRE
- Journal :
- The Journal of Pathology
- Accession number :
- edsair.doi.dedup.....5b7f4a7e72191b0c73356cf59acfe611