Conventional radiomics models often treat tumors as spatially homogeneous entities, limiting their ability to capture intratumoral heterogeneity and its impact on prognosis and treatment resistance. Habitat imaging addresses this limitation by explicitly mode...
Author profile
Misato Kishi
Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University
Habitat Imaging–Guided Drug Reversal Discovery In Head and Neck Cancer
Proffered Program · Therapy Physics
From Segmentation to Modeling Tumor Evolution: Trajectory-Aware Time-Series Learning (TRASE) for Adaptive Radiotherapy
Accurate delineation of the gross tumor volume of the primary lesion (GTVp) during radiotherapy is essential for ART, particularly in head-and-neck cancer where tumor regression and anatomical deformation occur during treatment. However, mid-treatment contour...
Poster Program · Therapy Physics
Image-to-Drug In Glioblastoma: Multi-Sequence MRI Radiomics Coupled with Deep Q-Network Drug Discovery
To develop an image-to-drug framework for glioblastoma (GBM) that translates multi-sequence MRI radiomics–based survival risk into actionable therapeutic hypotheses, by integrating ensemble survival modeling with multi-omics reinforcement learning.
Proffered Program · Therapy Physics