A Robust Training Method for Pathological Cellular Detector via Spatial Loss Calibration

Computer-aided diagnosis of pathological images usually requires detecting and examining all positive cells for accurate diagnosis. However, cellular datasets tend to be sparsely annotated due to the challenge of annotating all the cells. However, training detectors on sparse annotations may be misl...

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Detalles Bibliográficos
Autores principales: Li, Hansheng, Kang, Yuxin, Yang, Wentao, Wu, Zhuoyue, Shi, Xiaoshuang, Liu, Feihong, Liu, Jianye, Hu, Lingyu, Ma, Qian, Cui, Lei, Feng, Jun, Yang, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712578/
https://www.ncbi.nlm.nih.gov/pubmed/34970560
http://dx.doi.org/10.3389/fmed.2021.767625

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712578/
https://www.ncbi.nlm.nih.gov/pubmed/34970560
http://dx.doi.org/10.3389/fmed.2021.767625

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