Evaluating Cell Nuclei Segmentation for Use on Whole-Slide Images in Lung Cytology
2014 (English)In: 2014 22nd International Conference on Pattern Recognition (ICPR), IEEE Computer Society, 2014, 3380-3385 p.Conference paper (Refereed)
This paper presents results from an evaluation of three previously presented methods for segmentation of cell nuclei in lung cytology samples scanned by whole-slide scanners. Whole-slide images from seven cases of endobronchial ultrasound-guided transbronchial needle aspiration samples were used for extracting a number of regions of interest, in which approximately 2700 cell nuclei were manually segmented to form the ground truth. The segmented cells included benign bronchial epithelium, lymphocytes, granulocytes, histiocytes and malignant epithelial cells. The best results were obtained with a method based upon adaptive thresholding and an added step of clustering for distinguishing between cytoplasm and cell nuclei. This method achieved a mean DICE-score of 0.81 and a sensitivity and specificity of 0.88 and 0.81 respectively. In addition, this method was by far the fastest method, with a mean processing time of 7.8 s per image (2048 x 2048 pixels per image). By further improvements, such as lowering the false positive rate and using parallel computing hardware, this method has the potential to form the first building block in a system for computerized screening of whole-slide images in lung cytology.
Place, publisher, year, edition, pages
IEEE Computer Society, 2014. 3380-3385 p.
, International Conference on Pattern Recognition, ISSN 1051-4651
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:liu:diva-121334DOI: 10.1109/ICPR.2014.582ISI: 000359818003086ISBN: 978-1-4799-5208-3OAI: oai:DiVA.org:liu-121334DiVA: diva2:853445
22nd International Conference on Pattern Recognition (ICPR, Stockholm, Sweden, 24-28 Aug. 2014