Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy
Authors | |
---|---|
Year of publication | 2016 |
Type | Article in Proceedings |
Conference | Computer Vision -- ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part I |
MU Faculty or unit | |
Citation | |
web | http://dx.doi.org/10.1007/978-3-319-46604-0_23 |
Doi | http://dx.doi.org/10.1007/978-3-319-46604-0_23 |
Field | Informatics |
Keywords | Exosome; Detection; Segmentation; Transmission electron microscopy; Image processing |
Description | We presented a morphological method for automatic detection and segmentation of exosomes in transmission electron microscopy images. The exosome segmentation was carried out using morphological seeded watershed on gradient magnitude image, with the seeds established by applying a series of hysteresis thresholdings, followed by morphological filtering and cluster splitting. We tested the method on a diverse image data set, yielding the detection performance of slightly over 80 %. |
Related projects: |