{"id":"W2088707772","doi":"10.1118/1.4889083","title":"SU‐F‐BRF‐14: Increasing the Accuracy of Dose Calculation On Cone‐Beam Imaging Using Deformable Image Registration in the Case of Prostate Translation","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Hôtel-Dieu de Québec","funders":"","keywords":"Cone beam computed tomography; Image registration; Imaging phantom; Cone beam ct; Nuclear medicine; Translation (biology); Prostate; Medicine; Prostate cancer; Computer science; Radiation treatment planning; Centroid; Medical imaging; Fiducial marker; Computed tomography; Artificial intelligence; Radiology; Radiation therapy; Image (mathematics); Cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002371228,0.0007267476,0.0004832066,0.001179758,0.000286431,0.001047866,0.001527703,0.000898774,0.002519066],"category_scores_gemma":[0.007245773,0.0005662393,0.0007299581,0.000625857,0.0003802858,0.0008800647,0.0006695674,0.0007106061,0.0009438822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006282311,"about_ca_system_score_gemma":0.000771176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002097547,"about_ca_topic_score_gemma":0.001955204,"domain_scores_codex":[0.9984933,0.0002868669,0.0001085627,0.0002100282,0.0007972161,0.000103971],"domain_scores_gemma":[0.9978249,0.0006828617,0.0003476579,0.0005642048,0.0005123043,0.00006806546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001307631,0.000361336,0.01759399,0.0004370014,0.0002181779,0.0002738271,0.0002925794,0.04108527,0.2811925,0.001535109,0.004291077,0.6514114],"study_design_scores_gemma":[0.0001725103,0.0012398,0.04353441,0.00007332577,0.000187745,0.002960152,0.00004769178,0.4435435,0.4933336,0.001502909,0.0131903,0.0002140486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.360322,0.002285159,0.6176419,0.0004556414,0.000160636,0.0003243503,0.0004025821,0.01195128,0.006456483],"genre_scores_gemma":[0.5654958,0.0003309615,0.4292489,0.0001018365,0.00002789546,0.00009868525,0.0007222371,0.001610033,0.002363685],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002519066,"threshold_uncertainty_score":0.01254034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530331573419917,"score_gpt":0.2760724177066279,"score_spread":0.2607691019724287,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}