RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Jacob Antunes, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish Viswanath. RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. In Maxime Descoteaux, Lena Maier-Hein, Alfred Franz, Pierre Jannin, D. Louis Collins, Simon Duchesne, editors, Medical Image Computing and Computer Assisted Intervention - MICCAI 2017 - 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part II. Volume 10434 of Lecture Notes in Computer Science, pages 468-476, Springer, 2017. [doi]

The following publications are possibly variants of this publication:

RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to TreatmentJacob T. Antunes, Marwa Ismail, Imran Hossain, Zhoumengdi Wang, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath. titb, 26(6):2627-2636, 2022. [doi]

Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in GlioblastomaMarwa Ismail, Prateek Prasanna, Kaustav Bera, Volodymyr Statsevych, Virginia B. Hill, Gagandeep Singh, Sasan Partovi, Niha G. Beig, Sean D. McGarry, Peter S. LaViolette, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari. tmi, 41(7):1764-1777, 2022. [doi]

Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor PrognosisPrateek Prasanna, Jhimli Mitra, Niha Beig, Sasan Partovi, Gagandeep Singh, Marco Pinho, Anant Madabhushi, Pallavi Tiwari. miccai 2017: 459-467 [doi]

runs on WebDSL