Ensemble processing and convexity measure for abnormally shaped nuclei segmentation

Yue Han; Yang Lei; Viktor Shkolnikov; Daisy Xin; Alicia Auduong; Steven Barcelo; Jan Allebach; Edward J. Delp

doi:10.1117/12.3005617

2 April 2024 Ensemble processing and convexity measure for abnormally shaped nuclei segmentation

Yue Han, Yang Lei, Viktor Shkolnikov, Daisy Xin, Alicia Auduong, Steven Barcelo, Jan Allebach, Edward J. Delp

Proceedings Volume 12926, Medical Imaging 2024: Image Processing; 129261Y (2024) https://doi.org/10.1117/12.3005617
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Morphological abnormalities in biological cell nuclei are used as essential features for diagnosing diseases, determining cell cycle stages, and conducting other fundamental cell biological research. While many deep learning approaches have been proposed for segmenting normal elliptical nuclei, less work has been done on segmenting abnormally shaped nuclei. One issue is that acquiring a significant number of annotated nuclei data poses a challenge for many deep learning segmentation methods, particularly due to the generally high cost associated with obtaining annotated data. The lack of the use of shape analysis is another problem that causes segmentation to not perform well for abnormally shaped nuclei. To address these problems, we propose a system to segment abnormally shaped nuclei with limited training data. We generate synthetic ground truth images of abnormally shaped nuclei to supplement the limited amount of training images available. Six Mask R-CNNs are trained to segment abnormally shaped nuclei. We then introduce an ensemble strategy, known as Weighted Mask Fusion, to combine the segmentation results from the six Mask R-CNNs. We describe a shape analysis step, based on a convexity measure, that is used on the segmented nuclei in the ensemble result to further improve the segmentation performance. Our proposed system is compared with other segmentation methods for abnormally shaped nuclei. The evaluation demonstrates the effectiveness of the ensemble processing, fusion, and convexity measures for segmenting abnormally shaped nuclei.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yue Han, Yang Lei, Viktor Shkolnikov, Daisy Xin, Alicia Auduong, Steven Barcelo, Jan Allebach, and Edward J. Delp "Ensemble processing and convexity measure for abnormally shaped nuclei segmentation", Proc. SPIE 12926, Medical Imaging 2024: Image Processing, 129261Y (2 April 2024); https://doi.org/10.1117/12.3005617

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