Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma

Objective: To evaluate the feasibility and accuracy of machine learning based texture analysis of unenhanced CT images in differentiating subclinical pheochromocytoma (sPHEO) from lipid-poor adenoma (LPA) in adrenal incidentaloma (AI). Methods: Seventy-nine patients with 80 LPA and 29 patients with...

Descripción completa

Detalles Bibliográficos
Autores principales: Yi, Xiaoping, Guan, Xiao, Chen, Chen, Zhang, Youming, Zhang, Zhe, Li, Minghao, Liu, Peihua, Yu, Anze, Long, Xueying, Liu, Longfei, Chen, Bihong T, Zee, Chishing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2018
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171020/
https://www.ncbi.nlm.nih.gov/pubmed/30310515
http://dx.doi.org/10.7150/jca.26356

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171020/
https://www.ncbi.nlm.nih.gov/pubmed/30310515
http://dx.doi.org/10.7150/jca.26356

Ejemplares similares