Esther Van Poel, Pierre Vanden Bussche, Benoît Pétré, Cécile Ponsar, Claire Collins, Michel De Jonghe, Anne-Françoise Donneau, Nicolas Gillain, Michèle Guillaume, Sara Willems
Quality of care in Belgian general practices during the COVID-19 pandemic: results of the cross-sectional PRICOV-19 study
BMC primary care
nuclei segmentation fundamental prerequisite digital pathology workflow development automated methods nuclei segmentation enables quantitative analysis wide existence large variances nuclei morphometry histopathology images however manual annotation tens thousands nuclei tedious timeconsuming requires significant amount human effort domainspecific expertise alleviate problem paper propose weaklysupervised nuclei segmentation method requires partial point labels nuclei specifically propose novel boundary mining framework nuclei segmentation named bonus simultaneously learns nuclei interior boundary information point labels achieve goal propose novel boundary mining loss guides model learn boundary information exploring pairwise pixel affinity multipleinstance learning manner consider challenging problem ie partial point label propose nuclei detection module curriculum learning detect missing nuclei prior morphological knowledge proposed method validated three public datasets monuseg cpm conic datasets experimental results demonstrate superior performance method stateoftheart weaklysupervised nuclei segmentation methods code httpsgithubcomhustlinyibonus