A bottom-up approach for tumour differentiation in whole slide images of lung adenocarcinoma

Najah Alsubaie; Korsuk Sirinukunwattana; Shan E. Ahmed Raza; David Snead; Nasir Rajpoot

doi:10.1117/12.2293316

6 March 2018 A bottom-up approach for tumour differentiation in whole slide images of lung adenocarcinoma

Najah Alsubaie, Korsuk Sirinukunwattana, Shan E. Ahmed Raza, David Snead, Nasir Rajpoot

Proceedings Volume 10581, Medical Imaging 2018: Digital Pathology; 105810E (2018) https://doi.org/10.1117/12.2293316
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

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.

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Citation Download Citation

Najah Alsubaie, Korsuk Sirinukunwattana, Shan E. Ahmed Raza, David Snead, and Nasir Rajpoot "A bottom-up approach for tumour differentiation in whole slide images of lung adenocarcinoma", Proc. SPIE 10581, Medical Imaging 2018: Digital Pathology, 105810E (6 March 2018); https://doi.org/10.1117/12.2293316

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