Now showing items 1-5 of 5

    • A robust deformable image registration enhancement method based on radial basis function. 

      Yin, Fang-Fang; Liang, Xiao; Wang, Chunhao; Cai, Jing (Quantitative imaging in medicine and surgery, 2019-07)
      Background:To develop and evaluate a robust deformable image registration (DIR) enhancement method based on radial basis function (RBF) expansion. Methods:To improve DIR accuracy using sparsely available measured displacements, ...
    • Incorporating Case-Based Reasoning for Radiation Therapy Knowledge Modeling: A Pelvic Case Study. 

      Yin, Fang-Fang; Sheng, Yang; Zhang, Jiahan; Wang, Chunhao; Wu, Q Jackie; Ge, Yaorong (Technology in cancer research & treatment, 2019-01)
      Knowledge models in radiotherapy capture the relation between patient anatomy and dosimetry to provide treatment planning guidance. When treatment schemes evolve, existing models struggle to predict accurately. We propose ...
    • Knowledge-Based Statistical Inference Method for Plan Quality Quantification. 

      Wu, Qingrong; Salama, Joseph; Yin, Fang-Fang; Zhang, Jiang; Ge, Yaorong; Wang, Chunhao; Sheng, Yang; ... (9 authors) (Technology in cancer research & treatment, 2019-01)
      AIM:The aim of the study is to develop a geometrically adaptive and statistically robust plan quality inference method. METHODS AND MATERIALS:We propose a knowledge-based plan quality inference method that references to ...
    • Radiotherapy Treatment Assessment using DCE-MRI 

      Wang, Chunhao (2016)
      AbstractThe goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. ...
    • Spatial-temporal variability of radiomic features and its effect on the classification of lung cancer histology. 

      Cai, Jing; Hong, Julian; Kelsey, Christopher; Yin, Fang-Fang; Lafata, Kyle; Wang, Chunhao (Physics in medicine and biology, 2018-11-08)
      The purpose of this research was to study the sensitivity of Computed Tomography (CT) radiomic features to motion blurring and signal-to-noise ratios (SNR), and investigate its downstream effect regarding the classification ...