Polycystic liver: automatic segmentation using deep learning on CT is faster and as accurate compared to manual segmentation

被引：0
|
作者：
Bénédicte Cayot
Laurent Milot
Olivier Nempont
Anna S Vlachomitrou
Carole Langlois-Jacques
Jérôme Dumortier
Olivier Boillot
Karine Arnaud
Thijs R M Barten
Joost P H Drenth
Pierre-Jean Valette
机构：
[1] University of Lyon,Department of Medical Imaging, Hospices Civils de Lyon
[2] Hôpital Edouard Herriot,Service d’imagerie médicale et interventionnelle
[3] University of Lyon,Department of Medical Imaging, Edouard Herriot Hospital, Civil Hospices of Lyon
[4] Philips France,Department of Hepatology and Gastroenterology, Civil Hospices of Lyon
[5] Unit of Biostatistics,Department of Hepatobiliary
[6] Civil Hospices of Lyon,Pancreatic Surgery and Hepatology, Civil Hospices of Lyon
[7] Lyon ,Department of Gastroenterology and Hepatology
[8] CNRS UMR5558,undefined
[9] Laboratory of Biometry and Evolutionary Biology,undefined
[10] Biostatistics-Health Team,undefined
[11] Edouard Herriot Hospital,undefined
[12] Federation of Digestive Specialties,undefined
[13] University of Lyon,undefined
[14] University of Lyon,undefined
[15] Edouard Herriot Hospital,undefined
[16] University of Lyon,undefined
[17] Edouard Herriot Hospital,undefined
[18] Civil Hospices of Lyon,undefined
[19] Radboud University Medical Center,undefined
[20] Radboud University Medical Center,undefined
来源：
European Radiology | 2022年 / 32卷
关键词：
Deep learning; Biometry; Liver diseases; Cysts; Tomography, X-ray computed;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：4780 / 4790
页数：10
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