Prediction of histologic grade and type of small (< 4 cm) papillary renal cell carcinomas using texture and neural network analysis: a feasibility study.

Authors

Shawn Haji-Momenian, George Washington University
RyeAnne Ricker, George Washington University
Zirong Chen, George Washington University
Margaret Houser, George Washington University
Nagasai Adusumilli, George Washington University
Myung Yang, George Washington University
Antoun Toubaji, George Washington University
Murray Loew, George Washington University

Document Type

Journal Article

Publication Date

4-4-2021

Journal

Abdom Radiol (NY)

DOI

10.1007/s00261-021-03044-5

Keywords

Histology; Machine learning; Papillary renal cell carcinoma; Texture; Type.

APA Citation

Haji-Momenian, S., Ricker, R., Chen, Z., Houser, M., Adusumilli, N., Yang, M., Toubaji, A., & Loew, M. (2021). Prediction of histologic grade and type of small (< 4 cm) papillary renal cell carcinomas using texture and neural network analysis: a feasibility study.. Abdom Radiol (NY), (). http://dx.doi.org/10.1007/s00261-021-03044-5

Peer Reviewed

1