{"id":"W2140915205","doi":"10.1109/isbi.2006.1624955","title":"Fast fluid registration using inverse filtering for non-rigid image registration","year":2006,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Image registration; Computer science; Inverse; Computer vision; Artificial intelligence; Image (mathematics); Algorithm; Mathematics; Geometry","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":[0.001445306,0.0008578941,0.001087382,0.00146466,0.0006627479,0.001180093,0.0009282849,0.00155602,0.00217533],"category_scores_gemma":[0.003317587,0.000483047,0.001026569,0.0009289591,0.001032958,0.001814609,0.001679116,0.001350649,0.001296772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003949203,"about_ca_system_score_gemma":0.0008797814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008215553,"about_ca_topic_score_gemma":0.0009948062,"domain_scores_codex":[0.9990389,0.0002311044,0.00005707038,0.0001491124,0.000464227,0.00005965089],"domain_scores_gemma":[0.9989467,0.0004740749,0.0001017064,0.0002156998,0.0002178658,0.0000439098],"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":[0.0003521105,0.00009656812,0.0005455535,0.0003519131,0.000129542,0.0004133588,0.0002433847,0.052891,0.2640874,0.02239406,0.002610028,0.655885],"study_design_scores_gemma":[0.00007433356,0.0004837418,0.0010428,0.00004475376,0.00009316177,0.002182616,0.00007579735,0.7220726,0.2265143,0.01699879,0.03022179,0.0001952994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001745211,0.0001029855,0.9975165,0.00004240435,0.00003258897,0.0000191267,0.000005839432,0.0003270484,0.0002082566],"genre_scores_gemma":[0.0460511,0.0003034587,0.9515955,0.00006275832,0.00007388612,0.00007699026,0.00005662771,0.0001809962,0.001598611],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00217533,"threshold_uncertainty_score":0.00764364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02825921398671261,"score_gpt":0.3007084608214809,"score_spread":0.2724492468347683,"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."}}