Bai Li, Selene Valerino-Perea, Weiwen Zhou, Yihong Xie, Keith Syrett, Remco Peters, Zouyan He, Yunfeng Zou, Frank de Vocht, Charlie Foster
The impact of the world's first regulatory, multi-setting intervention on sedentary behaviour among children and adolescents (ENERGISE): a natural experiment evaluation
The international journal of behavioral nutrition and physical activity
morphometry sural nerve biopsies fibre diameter myelin thickness helps us understand underlying mechanism peripheral neuropathies however current clinical practice portion specimen measured manually labourintensive nature study aimed develop machine learningbased application inputs whole slide image wsi biopsied sural nerve automatically performs morphometric analyses application consists three supervised learning models 1 nerve fascicle instance segmentation 2 myelinated fibre detection 3 myelin sheath segmentation finetuned models using 86 toluidine bluestained slides various neuropathies developed opensource python library performance evaluation showed 1 mask average precision ap 0861 fascicle segmentation 2 box ap 0711 fibre detection 3 mean intersection union miou 0817 myelin segmentation software identified 323298 nerve fibres 782 fascicles 70 wsis small large fibre populations objectively determined based clustering analysis demyelination group large fibres thinner myelin sheaths higher gratios vasculitis group slope regression line scatter plots diameters gratios higher demyelination group vasculitis group developed application performs whole slide morphometry human biopsy samples opensource software used clinicians pathologists without specific machine learning skills expect facilitate datadriven analysis sural nerve biopsies detailed understanding diseases