Color standardization in whole slide imaging using a color calibration slide

Bautista, Pinky A.; Hashimoto, Noriaki; Yagi, Yukako

doi:10.4103/2153-3539.126153

Cited by 105 publications

(82 citation statements)

References 35 publications

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“…The staining correction we presented in this paper can be used in conjunction with the color calibration slide proposed in [29]. While the use of the color calibration slide ensures that the colors reproduced by the different slide scanners are consistent, the present staining correction scheme addresses the colorimetric differences in histopathology images which are mainly caused by staining variations in histology slides.…”

Section: Discussionmentioning

confidence: 99%

“…Previous works have shown that the accuracy of image analysis is sensitive to variations in the colorimetric attributes of the image [17,18,21,29,30]. The box plots in Fig.…”

Section: Tissue Classificationmentioning

confidence: 98%

“…For a fully automated implementation of the staining correction, automated extraction of these sample images should be considered. Also, since the determination of the maximum dye amount, c max , is sensitive to the presence of tissue artifacts, such as tissue folds which absorbed more dye than normal tissue areas, integration of methods that automatically detect the presence of tissue artifacts [29] and methods that automatically evaluate the image quality [34,35] is ideal.…”

Section: Limitations and Future Workmentioning

confidence: 99%

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Staining Correction in Digital Pathology by Utilizing a Dye Amount Table

Bautista

Yagi

2015

J Digit Imaging

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The stained colors of the tissue components are popularly used as features for image analysis. However, variations in the staining condition of the histology slides prompt variations to the color distribution of the stained tissue samples which could impact the accuracy of the analysis. In this paper, we present a method to correct the staining condition of a histology image. In the method, a look-up table (LUT) based on the dye amounts absorbed by the sample is built. The LUT can be built when either (i) the source and reference staining conditions are specified or (ii) when the user simply wants to recreate his/her preferred staining condition without specifying any reference slide. The effectiveness of the present method was evaluated in two aspects: (i) CIELAB color difference of nuclei, cytoplasm, and red blood cells, between the ten different slides of liver tissue, and (ii) classification of the different tissue components. Application of the present staining correction method reduced the color difference between the slides by an average factor of 9.8 and the classification performance of a linear discriminant classifier improved by 16.5 % on the average. Results of the paired t test statistical analysis further showed that the reduction in the CIELAB color difference between the slides and the improvement in the classifier's performance when staining correction was implemented is significant at p<0.001.

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Section: Discussionmentioning

confidence: 99%

“…Previous works have shown that the accuracy of image analysis is sensitive to variations in the colorimetric attributes of the image [17,18,21,29,30]. The box plots in Fig.…”

Section: Tissue Classificationmentioning

confidence: 98%

Section: Limitations and Future Workmentioning

confidence: 99%

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Staining Correction in Digital Pathology by Utilizing a Dye Amount Table

Bautista

Yagi

2015

J Digit Imaging

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“…[3] The high quality and consistency of whole slide images are becoming more important with an increase in the computer aided diagnostics. Recent works[456] propose methods to standardize color distribution of the whole slide images in a post-processing step. However, the workflow standardization is non-trivial mainly because it requires formalization of multiple processes, for example, specimen preparation, scanning, image postprocessing and displaying.…”

Section: Introductionmentioning

confidence: 99%

A quantitative approach to evaluate image quality of whole slide imaging scanners

Shrestha

Kneepkens

Vrijnsen

et al. 2016

Journal of Pathology Informatics

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Context:The quality of images produced by whole slide imaging (WSI) scanners has a direct influence on the readers’ performance and reliability of the clinical diagnosis. Therefore, WSI scanners should produce not only high quality but also consistent quality images.Aim:We aim to evaluate reproducibility of WSI scanners based on the quality of images produced over time and among multiple scanners. The evaluation is independent of content or context of test specimen.Methods:The ultimate judge of image quality is a pathologist, however, subjective evaluations are heavily influenced by the complexity of a case and subtle variations introduced by a scanner can be easily overlooked. Therefore, we employed a quantitative image quality assessment method based on clinically relevant parameters, such as sharpness and brightness, acquired in a survey of pathologists. The acceptable level of quality per parameter was determined in a subjective study. The evaluation of scanner reproducibility was conducted with Philips Ultra-Fast Scanners. A set of 36 HercepTest™ slides were used in three sub-studies addressing variations due to systems and time, producing 8640 test images for evaluation.Results:The results showed that the majority of images in all the sub-studies are within the acceptable quality level; however, some scanners produce higher quality images more often than others. The results are independent of case types, and they match our perception of quality.Conclusion:The quantitative image quality assessment method was successfully applied in the HercepTest™ slides to evaluate WSI scanner reproducibility. The proposed method is generic and applicable to any other types of slide stains and scanners.

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“…All these issues may interfere with image analysis algorithms [22]. Some recent advances have been done for color standardization in WSI by means of using a color calibration slide [23]. A solution to overcome tissue fold artifacts by color enhancement techniques has also been developed by the same authors [24].…”

Section: Image Analysis In Digital Pathologymentioning

confidence: 99%

New Trends of Emerging Technologies in Digital Pathology

et al. 2016

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The future paradigm of pathology will be digital. Instead of conventional microscopy, a pathologist will perform a diagnosis through interacting with images on computer screens and performing quantitative analysis. The fourth generation of virtual slide telepathology systems, so-called virtual microscopy and whole-slide imaging (WSI), has allowed for the storage and fast dissemination of image data in pathology and other biomedical areas. These novel digital imaging modalities encompass high-resolution scanning of tissue slides and derived technologies, including automatic digitization and computational processing of whole microscopic slides. Moreover, automated image analysis with WSI can extract specific diagnostic features of diseases and quantify individual components of these features to support diagnoses and provide informative clinical measures of disease. Therefore, the challenge is to apply information technology and image analysis methods to exploit the new and emerging digital pathology technologies effectively in order to process and model all the data and information contained in WSI. The final objective is to support the complex workflow from specimen receipt to anatomic pathology report transmission, that is, to improve diagnosis both in terms of pathologists' efficiency and with new information. This article reviews the main concerns about and novel methods of digital pathology discussed at the latest workshop in the field carried out within the European project AIDPATH (Academia and Industry Collaboration for Digital Pathology).

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Color standardization in whole slide imaging using a color calibration slide

Cited by 105 publications

References 35 publications

Staining Correction in Digital Pathology by Utilizing a Dye Amount Table

Staining Correction in Digital Pathology by Utilizing a Dye Amount Table

A quantitative approach to evaluate image quality of whole slide imaging scanners

New Trends of Emerging Technologies in Digital Pathology

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