Openhi: Open platform for histopathological image annotation

Pargorn Puttapirat, Haichuan Zhang, Jingyi Deng, Yuxin Dong, Jiangbo Shi, Peiliang Lou, Chunbao Wang, Lixia Yao, Xiangrong Zhang, Chen Li

Research output: Contribution to journalArticle

Abstract

Consolidating semantically rich annotation on digital histopathological images known as whole-slide images requires a software capable of handling such type of biomedical data with support for procedures which align with existing pathological protocols. Demands for large-scale annotated histopathological datasets are on the raise since they are needed for developments of artificial intelligence techniques to promote automated diagnosis, mass screening, phenotype-genotype association study, etc. This paper presents an open platform for efficient collaborative histopathological image annotation with standardised semantic enrichment at a pixel-level precision named OpenHI (Open Histopathological Image). The framework’s responsive processing algorithm can perform large-scale histopathological image annotation and serve as biomedical data infrastructure for digital pathology. Its web-based design is highly configurable and could be extended to annotate histopathological image of various oncological types. The framework is open-source and fully documented.

Original languageEnglish (US)
Pages (from-to)328-349
Number of pages22
JournalInternational Journal of Data Mining and Bioinformatics
Volume22
Issue number4
DOIs
StatePublished - Jan 1 2019

Fingerprint

Mass Screening
Artificial Intelligence
Pathology
Semantics
Artificial intelligence
Screening
Software
Pixels
Genotype
Processing
artificial intelligence
pathology
Datasets
MASS syndrome
semantics
infrastructure

Keywords

  • Cancer diagnosis
  • Cancer grading
  • Digital pathology
  • Genotype-phenotype association
  • Histopathology
  • Image annotation
  • OpenHI
  • Virtual magnification
  • Virtual slide
  • Whole-slide image
  • WSI

ASJC Scopus subject areas

  • Information Systems
  • Biochemistry, Genetics and Molecular Biology(all)
  • Library and Information Sciences

Cite this

Puttapirat, P., Zhang, H., Deng, J., Dong, Y., Shi, J., Lou, P., ... Li, C. (2019). Openhi: Open platform for histopathological image annotation. International Journal of Data Mining and Bioinformatics, 22(4), 328-349. https://doi.org/10.1504/IJDMB.2019.101393

Openhi : Open platform for histopathological image annotation. / Puttapirat, Pargorn; Zhang, Haichuan; Deng, Jingyi; Dong, Yuxin; Shi, Jiangbo; Lou, Peiliang; Wang, Chunbao; Yao, Lixia; Zhang, Xiangrong; Li, Chen.

In: International Journal of Data Mining and Bioinformatics, Vol. 22, No. 4, 01.01.2019, p. 328-349.

Research output: Contribution to journalArticle

Puttapirat, P, Zhang, H, Deng, J, Dong, Y, Shi, J, Lou, P, Wang, C, Yao, L, Zhang, X & Li, C 2019, 'Openhi: Open platform for histopathological image annotation', International Journal of Data Mining and Bioinformatics, vol. 22, no. 4, pp. 328-349. https://doi.org/10.1504/IJDMB.2019.101393
Puttapirat, Pargorn ; Zhang, Haichuan ; Deng, Jingyi ; Dong, Yuxin ; Shi, Jiangbo ; Lou, Peiliang ; Wang, Chunbao ; Yao, Lixia ; Zhang, Xiangrong ; Li, Chen. / Openhi : Open platform for histopathological image annotation. In: International Journal of Data Mining and Bioinformatics. 2019 ; Vol. 22, No. 4. pp. 328-349.
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