Detection of blur artifacts in histopathological whole-slide images of endomyocardial biopsies - PubMed (original) (raw)

Detection of blur artifacts in histopathological whole-slide images of endomyocardial biopsies

Hang Wu et al. Annu Int Conf IEEE Eng Med Biol Soc. 2015.

Abstract

Histopathological whole-slide images (WSIs) have emerged as an objective and quantitative means for image-based disease diagnosis. However, WSIs may contain acquisition artifacts that affect downstream image feature extraction and quantitative disease diagnosis. We develop a method for detecting blur artifacts in WSIs using distributions of local blur metrics. As features, these distributions enable accurate classification of WSI regions as sharp or blurry. We evaluate our method using over 1000 portions of an endomyocardial biopsy (EMB) WSI. Results indicate that local blur metrics accurately detect blurry image regions.

PubMed Disclaimer

Figures

Fig. 1

Fig. 1

Blur artifacts in an endomyocardial biospy (EMB) whole-slide images (WSI)

Fig. 2

Fig. 2

Classification of blurry and sharp images using histogram features of local blur metrics.

Fig. 3

Fig. 3

Histograms of local kurtosis in a blurry (a) and sharp (b) image.

Fig. 4

Fig. 4

Histograms of local average power spectrum in a blurry (a) and sharp image (b).

Fig. 5

Fig. 5

Histograms of local probablity metric in a blurry (a) and sharp image (b).

Fig. 6

Fig. 6

Local Pixel-Level metrics (red and orange) for detection of blurry images are more accurate compared to global metrics (blue). Results are consistent for a) KNN, b) NB, c) SVM, and d) RF; and for metrics F1-Score, Accuracy, and AUC.

Fig. 7

Fig. 7

Detection of image blur using local metric is sensitive to the size of neighbors used to calculate local metrics, as well as the number of histogram bins.

Similar articles

Cited by

References

    1. Kothari S, Phan JH, Stokes TH, Wang MD. Pathology imaging informatics for quantitative analysis of whole-slide images. Journal of the American Medical Informatics Association. 2013 amiajnl-2012-001540. - PMC - PubMed
    1. Gurcan MN, Boucheron LE, Can A, Madabhushi A, Rajpoot NM, Yener B. Histopathological image analysis: A review. Biomedical Engineering, IEEE Reviews in. 2009;2:147–171. - PMC - PubMed
    1. Stewart S, Winters GL, Fishbein MC, Tazelaar HD, Kobashigawa J, Abrams J, Andersen CB, Angelini A, Berry GJ, Burke MM. Revision of the 1990 working formulation for the standardization of nomenclature in the diagnosis of heart rejection. The Journal of heart and lung transplantation. 2005;24:1710–1720. - PubMed
    1. Ho J, Parwani AV, Jukic DM, Yagi Y, Anthony L, Gilbertson JR. Use of whole slide imaging in surgical pathology quality assurance: design and pilot validation studies. Human pathology. 2006;37:322–331. - PubMed
    1. Kothari S, Phan J, Wang M. Eliminating tissue-fold artifacts in histopathological whole-slide images for improved image-based prediction of cancer grade. Journal of Pathology Informatics. 2013;4:22. - PMC - PubMed

Publication types

MeSH terms

LinkOut - more resources