Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI

Dheerendranath Battalapalli; Apoorva Safai; Marwa Ismail; Virginia Hill; Volodymyr Statsevych; Raymond Huang; Manmeet Singh Ahluwalia; Pallavi Tiwari

doi:10.1109/ISBI56570.2024.10635456

Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI

Dheerendranath Battalapalli, Apoorva Safai, Marwa Ismail, Virginia Hill, Volodymyr Statsevych, Raymond Huang, Manmeet Singh Ahluwalia, Pallavi Tiwari

Baptist Health South Florida

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings
Publisher	IEEE Computer Society
ISBN (Electronic)	9798350313338
DOIs	https://doi.org/10.1109/ISBI56570.2024.10635456
State	Published - 2024
Event	21st IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Athens, Greece Duration: May 27 2024 → May 30 2024

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	21st IEEE International Symposium on Biomedical Imaging, ISBI 2024
Country/Territory	Greece
City	Athens
Period	5/27/24 → 5/30/24

ASJC Scopus Subject Areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Keywords

graph theory
Radiomics
tumor heterogeneity

Access to Document

10.1109/ISBI56570.2024.10635456

Cite this

Battalapalli, D., Safai, A., Ismail, M., Hill, V., Statsevych, V., Huang, R., Ahluwalia, M. S., & Tiwari, P. (2024). Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. In IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings (Proceedings - International Symposium on Biomedical Imaging). IEEE Computer Society. https://doi.org/10.1109/ISBI56570.2024.10635456

Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. / Battalapalli, Dheerendranath; Safai, Apoorva; Ismail, Marwa et al.
IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings. IEEE Computer Society, 2024. (Proceedings - International Symposium on Biomedical Imaging).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Battalapalli, D, Safai, A, Ismail, M, Hill, V, Statsevych, V, Huang, R, Ahluwalia, MS & Tiwari, P 2024, Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. in IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings. Proceedings - International Symposium on Biomedical Imaging, IEEE Computer Society, 21st IEEE International Symposium on Biomedical Imaging, ISBI 2024, Athens, Greece, 5/27/24. https://doi.org/10.1109/ISBI56570.2024.10635456

Battalapalli D, Safai A, Ismail M, Hill V, Statsevych V, Huang R et al. Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. In IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings. IEEE Computer Society. 2024. (Proceedings - International Symposium on Biomedical Imaging). doi: 10.1109/ISBI56570.2024.10635456

Battalapalli, Dheerendranath ; Safai, Apoorva ; Ismail, Marwa et al. / Graph-Radiomics Learning (GrRAiL) : Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings. IEEE Computer Society, 2024. (Proceedings - International Symposium on Biomedical Imaging).

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title = "Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI",

keywords = "graph theory, Radiomics, tumor heterogeneity",

author = "Dheerendranath Battalapalli and Apoorva Safai and Marwa Ismail and Virginia Hill and Volodymyr Statsevych and Raymond Huang and Ahluwalia, {Manmeet Singh} and Pallavi Tiwari",

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Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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