Quality Assurance Assessment of Diagnostic and Radiation Therapy–Simulation CT Image Registration for Head and Neck Radiation Therapy: Anatomic Region of Interest–based Comparison of Rigid and Deformable Algorithms

Abdallah Mohamed; Manee-Naad Ruangskul; Musaddiq Awan; Charles A. Baron; Jayashree Kalpathy–Cramer; Richard Castillo; Edward Castillo; Thomas Guerrero; Esengul Kocak–Uzel; Jinzhong Yang; Laurence E. Court; Michael Kantor; G. Brandon Gunn; Rivka R. Colen; Steven J. Frank; Adam S. Garden; David I. Rosenthal; Clifton D. Fuller

doi:10.1148/radiol.14132871

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Abstract

Development of a formal ROI-based QA workflow for registration assessment demonstrated improved performance with DIR techniques over RIR. After QA, DIR implementation should be the standard for head and neck diagnostic CT and simulation CT allineation, especially for target delineation.

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Mohamed et al. (2014) studied this question.

synapsesocial.com/papers/69eaf7a7da7b3d8040ef24fc https://doi.org/10.1148/radiol.14132871

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Quality Assurance Assessment of Diagnostic and Radiation Therapy–Simulation CT Image Registration for Head and Neck Radiation Therapy: Anatomic Region of Interest–based Comparison of Rigid and Deformable Algorithms

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Abstract

Discussion

Cite This Study

Quality Assurance Assessment of Diagnostic and Radiation Therapy–Simulation CT Image Registration for Head and Neck Radiation Therapy: Anatomic Region of Interest–based Comparison of Rigid and Deformable Algorithms

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Abstract

Discussion

Cite This Study

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