博莱霉素
表型
计算机断层摄影术
路径(计算)
路径分析(统计学)
病理
医学
放射科
人工智能
计算机科学
生物
基因
内科学
遗传学
机器学习
化疗
程序设计语言
作者
Ingrid Henneke,Christina Pilz,Jochen Wilhelm,Ioannis Alexopoulos,Aysan Ezaddoustdar,Regina Mukhametshina,Norbert Weißmann,Hossein Ardeschir Ghofrani,Friedrich Grimminger,Werner Seeger,Ralph T. Schermuly,Małgorzata Wygrecka,Baktybek Kojonazarov
出处
期刊:American Journal of Physiology-cell Physiology
[American Physical Society]
日期:2024-06-01
卷期号:326 (6): C1637-C1647
标识
DOI:10.1152/ajpcell.00708.2023
摘要
Microscopic computed tomography (µCT) imaging combined with an artificial intelligence (AI)-convolutional neural network (CNN)-powered lung segmentation is a rapid and powerful tool for noninvasive phenotyping of bleomycin mice over the course of the disease. This, in turn, allows earlier and more reliable identification of therapeutic effects of new drug candidates, ultimately leading to the reduction of unnecessary procedures in animals in pharmacological research.
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