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Proceedings Paper

A bottom-up approach for tumour differentiation in whole slide images of lung adenocarcinoma
Author(s): Najah Alsubaie; Korsuk Sirinukunwattana; Shan E. Ahmed Raza; David Snead; Nasir Rajpoot
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Paper Abstract

Analysis of tumour cells is essential for morphological characterisation which is useful for disease prognosis and survival prediction. Visual assessment of tumour cell morphology by expert human observers for prognostic purposes is subjective and potentially a tedious process. In this paper, we propose an automated and objective method for tumour cell analysis in whole slide images (WSI) of lung adenocarcinoma. Tumour cells are first extracted at higher magnification and then morphological, texture and spatial distribution features are computed for each cell. We investigated the biological impact of the nuclear features in the context of tumour grading. Results show that some of these features are correlated with tumour grade. We examine some of these features on the WSI where these features shows different distribution depends on the tumour grade.

Paper Details

Date Published: 6 March 2018
PDF: 10 pages
Proc. SPIE 10581, Medical Imaging 2018: Digital Pathology, 105810E (6 March 2018); doi: 10.1117/12.2293316
Show Author Affiliations
Najah Alsubaie, The Univ. of Warwick (United Kingdom)
Princess Nourah Univ. (Saudi Arabia)
Korsuk Sirinukunwattana, Institute of Biomedical Engineering, Univ. of Oxford (United Kingdom)
Shan E. Ahmed Raza, The Univ. of Warwick (United Kingdom)
The Institute of Cancer Research (United Kingdom)
David Snead, Univ. Hospitals Coventry and Warwickshire NHS Trust (United Kingdom)
Nasir Rajpoot, The Univ. of Warwick (United Kingdom)
Univ. Hospitals Coventry and Warwickshire (United Kingdom)


Published in SPIE Proceedings Vol. 10581:
Medical Imaging 2018: Digital Pathology
John E. Tomaszewski; Metin N. Gurcan, Editor(s)

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