TY - GEN
T1 - Cell segmentation using stable extremal regions in multi-exposure microscopy images
AU - Li, Mingzhong
AU - Yin, Zhaozheng
N1 - Publisher Copyright: © 2016 IEEE.
PY - 2016/6/15
Y1 - 2016/6/15
N2 - We propose a novel cell segmentation approach by extracting Multi-exposure Maximally Stable Extremal Regions (MMSER) in phase contrast microscopy images on the same cell dish. Using our method, cell regions can be well identified by considering the maximally stable regions with response to different camera exposure times. Meanwhile, halo artifacts with regard to cells at different stages are leveraged to identify cells' stages. The experimental results validate that high quality cell segmentation and cell stage classification can be achieved by our approach.
AB - We propose a novel cell segmentation approach by extracting Multi-exposure Maximally Stable Extremal Regions (MMSER) in phase contrast microscopy images on the same cell dish. Using our method, cell regions can be well identified by considering the maximally stable regions with response to different camera exposure times. Meanwhile, halo artifacts with regard to cells at different stages are leveraged to identify cells' stages. The experimental results validate that high quality cell segmentation and cell stage classification can be achieved by our approach.
KW - Maximally Stable Extremal Regions
KW - Microscopy
KW - cell segmentation
UR - https://www.scopus.com/pages/publications/84978412216
U2 - 10.1109/ISBI.2016.7493323
DO - 10.1109/ISBI.2016.7493323
M3 - Conference contribution
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 526
EP - 530
BT - 2016 IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society
T2 - 13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
Y2 - 13 April 2016 through 16 April 2016
ER -