{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003618693,0.00008484873,0.00007777126,0.00008004297,0.0001069665,0.0001995588,0.000378943,0.00003807515,0.00002341567],"category_scores_gemma":[0.00006395856,0.00007149242,0.00003587326,0.0001419809,0.00003025765,0.002463212,0.00007143064,0.00004853605,0.00001590353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008744491,"about_ca_system_score_gemma":0.00005875545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003862883,"about_ca_topic_score_gemma":0.00001349224,"domain_scores_codex":[0.9991148,0.00000996053,0.0002867856,0.0001780564,0.0002359542,0.0001744498],"domain_scores_gemma":[0.9993053,0.00002737483,0.000133715,0.0003377162,0.0001325025,0.00006340626],"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":[0.00001616258,0.0001163243,0.000113616,0.0001154585,0.00001470427,0.000001775811,0.001799913,0.0001489402,0.1383051,0.01099609,0.071148,0.7772239],"study_design_scores_gemma":[0.0003651544,0.00006836627,0.000133149,0.00001630301,0.000003477809,0.000009010271,0.00003068943,0.3043976,0.6898835,0.004132058,0.0008384307,0.0001223013],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00184315,0.000006428534,0.9931182,0.001422508,0.00006571471,0.0005382934,0.000003194847,0.0003168318,0.002685665],"genre_scores_gemma":[0.05125434,0.000006777996,0.9469693,0.0008395789,0.00007863873,0.00005397037,0.00001431348,0.000005979467,0.0007770828],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7771016,"threshold_uncertainty_score":0.2915376,"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."}}