{"id":"W4313146159","doi":"10.1109/icpr56361.2022.9956119","title":"Towards Positive Jacobian: Learn to Postprocess for Diffeomorphic Image Registration with Matrix Exponential","year":2022,"lang":"en","type":"article","venue":"2022 26th International Conference on Pattern Recognition (ICPR)","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Jacobian matrix and determinant; Image registration; Diffeomorphism; Artificial intelligence; Computer science; Computer vision; Regularization (linguistics); Deep learning; Algorithm; Mathematics; Image (mathematics); Applied mathematics; Pure mathematics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005056008,0.0002636511,0.0002230327,0.0003943434,0.0003299629,0.0004554746,0.001097184,0.00005516498,0.004082797],"category_scores_gemma":[0.0001155911,0.0002683724,0.00009709162,0.0003287721,0.00006621565,0.0006690664,0.0003290013,0.0003730016,0.0001267224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002554602,"about_ca_system_score_gemma":0.0002257708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001048198,"about_ca_topic_score_gemma":0.00003020155,"domain_scores_codex":[0.9969356,0.0001637166,0.0004688318,0.0007865524,0.001302411,0.0003428727],"domain_scores_gemma":[0.9982447,0.00009550716,0.0003475996,0.0003183392,0.0007946672,0.0001991646],"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":[0.001531673,0.001305827,0.0002534926,0.0001297161,0.0002812756,0.0002687481,0.002845933,0.00007430738,0.07981456,0.0143026,0.02260196,0.8765899],"study_design_scores_gemma":[0.01539206,0.02132084,0.008047799,0.0013069,0.0002418948,0.0008865441,0.005935131,0.1574313,0.7214882,0.05642846,0.006036241,0.005484627],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01190939,0.000004477048,0.9716996,0.01000417,0.0006829761,0.001046759,0.0008307,0.0002561811,0.00356578],"genre_scores_gemma":[0.9250428,0.0000170062,0.06158822,0.007108695,0.0002654997,0.002234825,0.002198185,0.00004797909,0.001496789],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9131334,"threshold_uncertainty_score":0.9999769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0466441125091908,"score_gpt":0.3235939397826555,"score_spread":0.2769498272734647,"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."}}