Classification of primary cilia in microscopy images using convolutional neural random forests

Sundaresh Ram, Mohammed S. Majdi, Jeffrey J. Rodriguez, Yang Gao, Heddwen L. Brooks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Accurate detection and classification of primary cilia in microscopy images is an essential and fundamental task for many biological studies including diagnosis of primary ciliary dyskinesia. Manual detection and classification of individual primary cilia by visual inspection is time consuming, and prone to induce subjective bias. However, automation of this process is challenging as well, due to clutter, bleed-through, imaging noise, and the similar characteristics of the non-cilia candidates present within the image. We propose a convolutional neural random forest classifier that combines a convolutional neural network with random decision forests to classify the primary cilia in fluorescence microscopy images. We compare the performance of the proposed classifier with that of an unsupervised k-means classifier and a supervised multi-layer perceptron classifier on real data consisting of 8 representative cilia images, containing more than 2300 primary cilia using precision/recall rates, ROC curves, AUC, and Fβ-score for classification accuracy. Results show that our proposed classifier achieves better classification accuracy.

Original languageEnglish (US)
Title of host publication2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages89-92
Number of pages4
ISBN (Electronic)9781538665688
DOIs
StatePublished - Sep 21 2018
Event2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018 - Las Vegas, United States
Duration: Apr 8 2018Apr 10 2018

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
Volume2018-April

Other

Other2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018
CountryUnited States
CityLas Vegas
Period4/8/184/10/18

Keywords

  • Image classification
  • confocal microscopy
  • convolutional neural network
  • primary cilia
  • random forests

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Classification of primary cilia in microscopy images using convolutional neural random forests'. Together they form a unique fingerprint.

  • Cite this

    Ram, S., Majdi, M. S., Rodriguez, J. J., Gao, Y., & Brooks, H. L. (2018). Classification of primary cilia in microscopy images using convolutional neural random forests. In 2018 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2018 - Proceedings (pp. 89-92). [8470320] (Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation; Vol. 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSIAI.2018.8470320