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Results for "topological features": 4 found

3D Topological Features for Outcome Assessment of Therapeutic Responses to Neoadjuvant Chemoradiotherapy (NCRT) with and without Anti-CD40 Immunotherapy in Local Advanced Rectal Cancer (LARC)

Authors: Todd A Aguilera, Gaurav Khatri, Jiaqi Liu, Hao Peng, Nina N. Sanford, Robert Timmerman, Haozhao Zhang

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, UT southwestern medical center, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose:
This study first integrates 3D topological data analysis with radiomics from local advanced rectal cancer T2-weighted MRI to evaluate therapeutic responses and quantify treatment-induced c...

A Topological Technique to Unify Image Texture and Morphology to Enhance Radiomic Feature Representations

Authors: David Brizel, Kyle J. Lafata, Jian-Guo Liu, Yvonne M Mowery, Yvonne M Mowery, William Paul Segars, Jack B Stevens

Affiliation: Department of Physics, Duke University, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Duke University, Department of Radiation Oncology, Duke University, University of Pittsburgh

Abstract Preview: Purpose: To develop a technique to quantify tumor topology using a unifying mathematical framework that integrates texture and morphology and to evaluate its feasibility as a prognostic biomarker for ...

Lymphocytic Feature Characterization Using a Deep Learning Algorithm on Post-Radiation Lymph Nodes

Authors: Rico Castillo, Katherine Gonzalez, Casey C. Heirman, Kyle J. Lafata, Casey Y. Lee, Xiang Li, Yvonne M Mowery, Yvonne M Mowery, Daniel Murphy, Allison Pittman, Ashlyn G. Rickard

Affiliation: Duke University, Department of Radiation Oncology, Duke University, University of Pittsburgh

Abstract Preview: Purpose: To evaluate the ability of a deep learning model to identify pathomic features in lymph nodes of preclinical head and neck squamous cell carcinoma (HNSCC) models as surrogates for predicting ...

Quantitative Fluorescence Imaging and Spatial Transcriptomics Reveal Compartment-Specific Immune Dynamics in HPV+ Oropharyngeal Cancer

Authors: Casey C. Heirman, Kyle J. Lafata, Xiang Li, Breylon Riley, Jack B Stevens, Tammara Watts

Affiliation: Duke University, Department of Radiation Oncology, Duke University

Abstract Preview: Purpose: To leverage quantitative fluorescence imaging and spatial transcriptomics for characterizing the spatial and molecular heterogeneity of the tumor microenvironment (TME) in HPV+ head and neck ...