Automated image analysis of nuclear atypia in high-power field histopathological image

Journal of Microscopy
Cheng LuMrinal Mandal

Abstract

We developed a computer-aided technique to study nuclear atypia classification in high-power field haematoxylin and eosin stained images. An automated technique for nuclear atypia score (NAS) calculation is proposed. The proposed technique uses sophisticated digital image analysis and machine-learning methods to measure the NAS for haematoxylin and eosin stained images. The proposed technique first segments all nuclei regions. A set of morphology and texture features is extracted from presegmented nuclei regions. The histogram of each feature is then calculated to characterize the statistical information of the nuclei. Finally, a support vector machine classifier is applied to classify a high-power field image into different nuclear atypia classes. A set of 1188 digital images was analysed in the experiment. We successfully differentiated the high-power field image with NAS1 versus non-NAS1, NAS2 versus non-NAS2 and NAS3 versus non-NAS3, with area under receiver-operating characteristic curve of 0.90, 0.86 and 0.87, respectively. In three classes evaluation, the average classification accuracy was 78.79%. We found that texture-based feature provides best performance for the classification. The automated technique is able to qua...Continue Reading

References

Feb 5, 2008·IEEE Transactions on Neural Networks·Chih-Wei Hsu, Chih-Jen Lin
Feb 16, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·X Tang
Mar 15, 2008·Pediatric and Developmental Pathology : the Official Journal of the Society for Pediatric Pathology and the Paediatric Pathology Society·Anna Maria Buccoliero
Jan 1, 2009·IEEE Reviews in Biomedical Engineering·Metin N GurcanB Yener
May 23, 2012·IEEE Journal of Biomedical and Health Informatics·Cheng LuMrinal Mandal
Jun 15, 2013·Journal of Pathology Informatics·Humayun IrshadFrédérique Capron
Mar 13, 2014·IEEE Journal of Biomedical and Health Informatics·Cheng Lu, Mrinal Mandal
Jan 1, 2010·Machine Learning in Medical Imaging·Marc NiethammerNancy E Thomas

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Citations

Oct 23, 2018·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Asha DasS David Peter
Apr 3, 2021·Biomedical Optics Express·Yudi LiuHui Ma

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