{"id":"W2941217945","doi":"10.1007/s11548-019-01932-2","title":"Deformable multimodal registration for navigation in beating-heart cardiac surgery","year":2019,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Image registration; Ultrasound; Artificial intelligence; Medicine; Affine transformation; Computer vision; Computer science; Similarity (geometry); Radiology; Image (mathematics); Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006358211,0.0005506305,0.000627001,0.001150244,0.0003723939,0.001060972,0.0007179172,0.0009493663,0.002737985],"category_scores_gemma":[0.002111369,0.0004535996,0.0006609304,0.001087839,0.0003651525,0.0008669734,0.0009726482,0.0009469413,0.00113127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003304538,"about_ca_system_score_gemma":0.0009376536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002442589,"about_ca_topic_score_gemma":0.003641751,"domain_scores_codex":[0.9996669,0.00009431478,0.00002699279,0.00006739384,0.0001136259,0.00003080886],"domain_scores_gemma":[0.9996377,0.0001359837,0.00005494314,0.00007477556,0.00007400179,0.00002257134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005496013,0.0001635389,0.003077255,0.0003662659,0.0001310373,0.0003128479,0.0003212557,0.04920175,0.1353218,0.004948887,0.00430073,0.8013052],"study_design_scores_gemma":[0.00003935264,0.0003506506,0.009433139,0.0001152318,0.0001798445,0.001870659,0.0001780835,0.8665864,0.1008475,0.00682682,0.01345589,0.0001166156],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05253054,0.001998012,0.9394379,0.0002965354,0.0001253035,0.0001189798,0.0002494239,0.002530477,0.002712855],"genre_scores_gemma":[0.5032467,0.002140661,0.485847,0.0002532464,0.00012522,0.0001917068,0.0006696926,0.001056616,0.006469174],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002737985,"threshold_uncertainty_score":0.009159505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01694739577455843,"score_gpt":0.2857382328817085,"score_spread":0.26879083710715,"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."}}