Ontology highlight
ABSTRACT:
SUBMITTER: Segawa M
PROVIDER: S-EPMC7283135 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Segawa Mayuko M Wolf Dane M DM Hultgren Nan W NW Williams David S DS van der Bliek Alexander M AM Shackelford David B DB Liesa Marc M Shirihai Orian S OS
Life science alliance 20200604 7
Recent breakthroughs in live-cell imaging have enabled visualization of cristae, making it feasible to investigate the structure-function relationship of cristae in real time. However, quantifying live-cell images of cristae in an unbiased way remains challenging. Here, we present a novel, semi-automated approach to quantify cristae, using the machine-learning Trainable Weka Segmentation tool. Compared with standard techniques, our approach not only avoids the bias associated with manual thresho ...[more]