{"id":"W1991691155","doi":"10.1117/12.467198","title":"Nonrigid mammogram registration using mutual information","year":2002,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Mutual information; Computer science; Artificial intelligence; Centroid; Image registration; Computer vision; Point set registration; Matching (statistics); Pattern recognition (psychology); Similarity (geometry); Landmark; Transformation (genetics); Spline (mechanical); Similarity measure; Point (geometry); Image (mathematics); Mathematics; Statistics","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":[0.002156825,0.0008984918,0.001115107,0.002668076,0.0005615989,0.001332314,0.001417351,0.0008966117,0.001621155],"category_scores_gemma":[0.006573,0.0007502267,0.001267015,0.002039171,0.001231793,0.002149661,0.002719921,0.0006807019,0.0008588732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006506999,"about_ca_system_score_gemma":0.0007388481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001026402,"about_ca_topic_score_gemma":0.001228892,"domain_scores_codex":[0.9971636,0.000839886,0.0001772882,0.0004735031,0.001232427,0.0001133593],"domain_scores_gemma":[0.9980022,0.0007734275,0.0003768738,0.0005851953,0.0002204121,0.0000418154],"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":[0.0004755631,0.0001071009,0.001289683,0.0003373837,0.000249964,0.0002851174,0.0003652164,0.154718,0.07371536,0.02410303,0.001916697,0.7424368],"study_design_scores_gemma":[0.00003898491,0.0003156425,0.003570582,0.00004240231,0.000106894,0.001103431,0.000100215,0.8586393,0.0935185,0.03206335,0.01036309,0.0001375006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0067943,0.0002343672,0.9914333,0.00005521499,0.00001478634,0.0000449644,0.00002739196,0.0007276766,0.0006679412],"genre_scores_gemma":[0.2422365,0.0005281643,0.7543433,0.0000668404,0.00005408304,0.0001675708,0.0002573604,0.0003978872,0.001948265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002668076,"threshold_uncertainty_score":0.01140654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463722919284243,"score_gpt":0.2117921902531272,"score_spread":0.1971549610602848,"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."}}