An automatic entropy method to efficiently mask histology whole-slide images

Abstract

Background: Tissue segmentation of histology whole-slide images (WSI) remains a critical task in automated digital pathology workflows for both accurate disease diagnosis and deep phenotyping for research purposes. This is especially challenging when the tissue structure of biospecimens is relatively porous and heterogeneous, such as for atherosclerotic plaques. Methods: In this study, we developed a unique approach called EntropyMasker based on image entropy to tackle the fore- and background segmentation (masking) task in histology WSI. We evaluated our method on 97 high-resolution WSI of human carotid atherosclerotic plaques in the Athero-Express Biobank Study, constituting hematoxylin and eosin (H&E) and 8 other staining types. Results and Conclusion: Using multiple benchmarking metrics, we compared our method with four widely used segmentation methods: Otsu's method, Adaptive mean, Adaptive Gaussian and slideMask and observed that our method had the highest sensitivity and Jaccard similarity index. We envision EntropyMasker to fill an important gap in WSI preprocessing and deep learning image analysis pipelines and enable disease phenotyping beyond the field of atherosclerosis.

Competing Interest Statement

Dr. Sander W. van der Laan has received Roche funding for unrelated work. Dr Craig A. Glastonbury has stock options in BenevolentAI and is a paid consultant for BenevolentAI, unrelated to this work. Dr. Clint L. Miller has received AstraZeneca funding for unrelated work.

Funding Statement

Funding for this research was provided by National Institutes of Health (NIH) grant nos. R00HL125912 and R01HL14823 (to CLM), and a Leducq Foundation Transatlantic Network of Excellence ('PlaqOmics') grant no. 18CVD02 (to CLM and SWvdL), and EU H2020 TO_AITION grant no. 848146 (to SWvdL).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Ethics committee, Medisch Ethische Toetsingscommissie (METC) Utrecht, at the University Medical Center Utrecht reviewed and provided ethical approval for this work involving human participants. All patients/participants provided their written informed consent to participate in this study.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

Yes

Data Availability

The histological data as used here are available through https://doi.org/10.34894/GN4YOS. All documented code and tutorial to run EntropyMasker can be found here https://github.com/CirculatoryHealth/EntropyMasker.

留言 (0)

沒有登入
gif