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TH-CD-303-04: A Method for Assessing Ground-Truth Accuracy of a Motion Model Based 4DCT Technique

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Purpose: To develop a technique that validates a breathing motion model and its reconstructed phase-specific image generation process using the original free-breathing images as ground truths. Methods: 16 lung cancer patients underwent the published protocol where 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. The first image was arbitrarily selected as the reference image. For constructing patient-specific lung motion model, state-of-the-art deformable image registration was employed to determine lung tissue displacement. The motion model was used, along with the free-breathing phase information of the original 25 image datasets, to generate a set of deformation vector fields (DVF) that mapped the reference image to the 24 non-reference images. The set of original images was simulated by applying the inverted model DVF to the reference image. To test the robustness of model simulation over the entire lung region, the model simulated imag

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Purpose: To develop a technique that validates a breathing motion model and its reconstructed phase-specific image generation process using the original free-breathing images as ground truths. Methods: 16 lung cancer patients underwent the published protocol where 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. The first image was arbitrarily selected as the reference image. For constructing patient-specific lung motion model, state-of-the-art deformable image registration was employed to determine lung tissue displacement. The motion model was used, along with the free-breathing phase information of the original 25 image datasets, to generate a set of deformation vector fields (DVF) that mapped the reference image to the 24 non-reference images. The set of original images was simulated by applying the inverted model DVF to the reference image. To test the robustness of model simulation over the entire lung region, the model simulated imag

Keywords

Ground truthImage registrationArtificial intelligenceComputer visionBreathingStandard deviationComputer scienceRobustness (evolution)

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