Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma

OBJECTIVE: To evaluate the value of 2-dimensional (2D) and 3-dimensional (3D) computed tomography texture analysis (CTTA) models in distinguishing fat-poor angiomyolipoma (fpAML) from chromophobe renal cell carcinoma (chRCC). METHODS: We retrospectively enrolled 32 fpAMLs and 24 chRCCs. Texture feat...

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Bibliografiset tiedot
Julkaisussa:Mol Imaging
Päätekijät: Yang, Guangjie, Gong, Aidi, Nie, Pei, Yan, Lei, Miao, Wenjie, Zhao, Yujun, Wu, Jie, Cui, Jingjing, Jia, Yan, Wang, Zhenguang
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: SAGE Publications 2019
Aiheet:
Artificial Intelligence in Molecular Imaging Clinics
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC6801892/
https://ncbi.nlm.nih.gov/pubmed/31625454
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/1536012119883161
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