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

页码：4780 / 4790

页数：10

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