{"id":"W2108589375","doi":"10.1007/978-3-642-15705-9_42","title":"A Parameterization of Deformation Fields for Diffeomorphic Image Registration and Its Application to Myocardial Delineation","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"St Joseph's Health Care; University Hospital","funders":"","keywords":"Jacobian matrix and determinant; Diffeomorphism; Regularization (linguistics); Image registration; Vector field; Transformation (genetics); Curl (programming language); Computer science; Artificial intelligence; Computer vision; Algorithm; Mathematics; Topology (electrical circuits); Image (mathematics); Applied mathematics; Geometry; Mathematical analysis","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":[0.002040255,0.0009775623,0.001243065,0.002163491,0.0005667984,0.001692347,0.001189474,0.001593829,0.002055007],"category_scores_gemma":[0.006602936,0.0008589743,0.001396299,0.002786504,0.001080207,0.001645665,0.001365042,0.002202511,0.001226034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006747617,"about_ca_system_score_gemma":0.000899443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001290939,"about_ca_topic_score_gemma":0.001065991,"domain_scores_codex":[0.9991556,0.0003139648,0.00009609719,0.0001898648,0.0002044043,0.00004002135],"domain_scores_gemma":[0.9982248,0.0007277183,0.0002241227,0.0004383865,0.0003151418,0.00006993405],"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":[0.0001689838,0.0001166245,0.0006126559,0.0002397275,0.00007555377,0.0001347894,0.0002333425,0.1540285,0.06716047,0.09167247,0.003669139,0.6818877],"study_design_scores_gemma":[0.00003260887,0.0001850794,0.001265524,0.00006278873,0.000059149,0.0005682948,0.00006557544,0.9140564,0.01989064,0.04776357,0.01593781,0.0001124936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001783223,0.0000893546,0.9976312,0.00004766742,0.00001307358,0.00002425046,0.00003183206,0.0001904591,0.000188822],"genre_scores_gemma":[0.07476449,0.0005884414,0.9217467,0.00006809444,0.00007809821,0.0002489264,0.000309632,0.0008594438,0.001336148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002163491,"threshold_uncertainty_score":0.01078999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01216483840831789,"score_gpt":0.3041541133962783,"score_spread":0.2919892749879604,"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."}}