期刊
2019 MEDICAL TECHNOLOGIES CONGRESS (TIPTEKNO)
卷 -, 期 -, 页码 200-203出版社
IEEE
DOI: 10.1109/tiptekno.2019.8895080
关键词
phase contrast optical microscopy; time series; cell segmentation; deep learning; SegNet
Phase contrast optical microscopy is a preferred imaging technique for live-cell, temporal analysis. Segmentation of cells from time series data acquired with this technique is a labor-intensive and time-consuming task that cell biology researchers need solution for. In this study traditional image processing and deep learning based approaches for automated cell segmentation from phase contrast optical microscopy time series are presented, and their performances are evaluated against manually annotated datasets.
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