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A Bayesian deep segmentation framework for glioblastoma tumor segmentation using follow-up MRIs

  • Tanjida Kabir
  • , Kang Lin Hsieh
  • , Luis Nunez
  • , Yu Chun Hsu
  • , Juan C. Rodriguez Quintero
  • , Octavio Arevalo
  • , Kangyi Zhao
  • , Jay Jiguang Zhu
  • , Roy F. Riascos
  • , Mahboubeh Madadi
  • , Xiaoqian Jiang
  • , Shayan Shams
  • Department of Health Data Science and Artificial Intelligence
  • University of Texas Health Science Center at Houston
  • Center for Secure Artificial Intelligence For HealthCare
  • University of Texas Medical School
  • Louisiana State University Health Sciences Center
  • Department of Statistics
  • University of Pittsburgh

Research output: Contribution to journal › Article › peer-review

Original languageEnglish
Article number1630245
JournalFrontiers in Neuroimaging
Volume4
DOIs
StatePublished - 2025
Externally publishedYes

ASJC Scopus Subject Areas

  • Neuroscience (miscellaneous)
  • Radiology Nuclear Medicine and imaging

Keywords

  • Bayesian deep learning
  • brain tumor segmentation
  • glioblastoma
  • machine learning
  • magnetic resonance imaging

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