Quantitative diagnosis of bladder cancer by morphometric analysis of HE images

Binlin Wu; Samantha V. Nebylitsa; Sushmita Mukherjee; Manu Jain

doi:10.1117/12.2083559

26 February 2015 Quantitative diagnosis of bladder cancer by morphometric analysis of HE images

Binlin Wu, Samantha V. Nebylitsa, Sushmita Mukherjee, Manu Jain

Proceedings Volume 9303, Photonic Therapeutics and Diagnostics XI; 930317 (2015) https://doi.org/10.1117/12.2083559
Event: SPIE BiOS, 2015, San Francisco, California, United States

Abstract

In clinical practice, histopathological analysis of biopsied tissue is the main method for bladder cancer diagnosis and prognosis. The diagnosis is performed by a pathologist based on the morphological features in the image of a hematoxylin and eosin (HE) stained tissue sample. This manuscript proposes algorithms to perform morphometric analysis on the HE images, quantify the features in the images, and discriminate bladder cancers with different grades, i.e. high grade and low grade. The nuclei are separated from the background and other types of cells such as red blood cells (RBCs) and immune cells using manual outlining, color deconvolution and image segmentation. A mask of nuclei is generated for each image for quantitative morphometric analysis. The features of the nuclei in the mask image including size, shape, orientation, and their spatial distributions are measured. To quantify local clustering and alignment of nuclei, we propose a 1-nearest-neighbor (1-NN) algorithm which measures nearest neighbor distance and nearest neighbor parallelism. The global distributions of the features are measured using statistics of the proposed parameters. A linear support vector machine (SVM) algorithm is used to classify the high grade and low grade bladder cancers. The results show using a particular group of nuclei such as large ones, and combining multiple parameters can achieve better discrimination. This study shows the proposed approach can potentially help expedite pathological diagnosis by triaging potentially suspicious biopsies.

Citation Download Citation

Binlin Wu, Samantha V. Nebylitsa, Sushmita Mukherjee, and Manu Jain "Quantitative diagnosis of bladder cancer by morphometric analysis of HE images", Proc. SPIE 9303, Photonic Therapeutics and Diagnostics XI, 930317 (26 February 2015); https://doi.org/10.1117/12.2083559

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available