{"id":"W1922796982","doi":"10.1109/nafips.2005.1548506","title":"Non-Rigid Registration using Free-Form Deformation for Prostate Images","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Image registration; Free-form deformation; Computer vision; Computer science; Artificial intelligence; Prostate; Similarity (geometry); Prostate brachytherapy; Mutual information; Deformation (meteorology); Similarity measure; Brachytherapy; Image (mathematics); Medicine; Radiology; Radiation therapy; Geography","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":[0.0009499554,0.0006994262,0.000889765,0.001312089,0.000458698,0.001021768,0.0008780077,0.001016277,0.002130092],"category_scores_gemma":[0.003329898,0.0004620818,0.001145333,0.001248426,0.0007077391,0.001372535,0.001232698,0.0007566196,0.00181255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004799672,"about_ca_system_score_gemma":0.0008257937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008877081,"about_ca_topic_score_gemma":0.001220432,"domain_scores_codex":[0.9987225,0.0003570581,0.00008019649,0.000247754,0.0005419388,0.00005043186],"domain_scores_gemma":[0.999173,0.0002585133,0.0001138995,0.000318282,0.0001119587,0.00002431208],"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":[0.0001913617,0.00008818844,0.0006722203,0.0002526813,0.0001346873,0.0002133514,0.0001715912,0.1435355,0.1650576,0.02766872,0.002152806,0.6598613],"study_design_scores_gemma":[0.00002852469,0.0002406366,0.003092905,0.00002938075,0.0000483585,0.001015195,0.00004439908,0.849013,0.09938107,0.02598316,0.02101299,0.0001103257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00326606,0.000135263,0.9954584,0.00004043799,0.00001795298,0.00002755415,0.00002012111,0.0006148018,0.000419315],"genre_scores_gemma":[0.1091528,0.0005602125,0.8863606,0.00007001785,0.00004833529,0.0001469217,0.0003059683,0.0004161384,0.002938956],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002130092,"threshold_uncertainty_score":0.007125854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02208860374865308,"score_gpt":0.3066149625590769,"score_spread":0.2845263588104238,"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."}}