Interactive Computer-assisted Approach for Evaluation of Ultrastructural Cilia Abnormalities

  • Introduction – Diagnosis of abnormal cilia function is based on ultrastructural analysis of axoneme defects, especialy the features of inner and outer dynein arms which are the motors of ciliar motility. Sub-optimal biopsy material, methodical, and intrinsic electron microscopy factors pose difficulty in ciliary defects evaluation. We present a computer-assisted approach based on state-of-the-art image analysis and object recognition methods yielding a time-saving and efficient diagnosis of cilia dysfunction. Method – The presented approach is based on a pipeline of basal image processing methods like smoothing, thresholding and ellipse fitting. However, integration of application specific knowledge results in robust segmentations even in cases of image artifacts. The method is build hierarchically starting with the detection of cilia within the image, followed by the detection of nine doublets within each analyzable cilium, and ending with the detection of dynein arms of each doublet. The process is concluded by a rough classification of the dynein arms as basis for a computer-assisted diagnosis. Additionally, the interaction possibilities are designed in a way, that the results are still reproducible given the completion report. Results – A qualitative evaluation showed reasonable detection results for cilia, doublets and dynein arms. However, since a ground truth is missing, the variation of the computer-assisted diagnosis should be within the subjective bias of human diagnosticians. The results of a first quantitative evaluation with five human experts and six images with 12 analyzable cilia showed, that with default parameterization 91.6% of the cilia and 98% of the doublets were found. The computer-assisted approach rated 66% of those inner and outer dynein arms correct, where all human experts agree. However, especially the quality of the dynein arm classification may be improved in future work.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Christoph PalmORCiDGND, Heiko Siegmund, Matthias Semmelmann, Claudia Grafe, Matthias Evert, Josef A. Schröder
DOI:https://doi.org/10.1117/12.2214976
Parent Title (English):Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February - 3 March, SPIE Proceedings 97853N, 2016, ISBN 9781510600201
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2016
Release Date:2019/12/20
Tag:Biopsy; Computer aided diagnosis and therapy; Electron microscopy; Image analysis; Image classification; Image processing; Image segmentation
GND Keyword:Zilie; Ultrastruktur; Anomalie; Bildverarbeitung; Objekterkennung; Computerunterstütztes Verfahren
Pagenumber:7
Institutes:Fakultät Informatik und Mathematik
Regensburg Center of Biomedical Engineering - RCBE
Regensburg Medical Image Computing - ReMIC
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke