{"id":"W2023743679","doi":"10.1016/j.media.2008.10.004","title":"Phase unwrapping of MR images using ΦUN – A fast and robust region growing algorithm","year":2008,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":92,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Friedrich-Schiller-Universität Jena","keywords":"Algorithm; Computer science; Phase unwrapping; Artificial intelligence; Signal-to-noise ratio (imaging); Image resolution; Noise (video); Phase (matter); Imaging phantom; Computer vision; Image (mathematics); Physics; Optics; Interferometry","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":[0.00110327,0.0009173493,0.0007681136,0.001105192,0.0004693204,0.001034577,0.001052374,0.001013328,0.001906133],"category_scores_gemma":[0.004282804,0.0007662344,0.0008010059,0.00118583,0.0005481294,0.001829818,0.001247438,0.001221825,0.001509687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002481659,"about_ca_system_score_gemma":0.0009303432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001061763,"about_ca_topic_score_gemma":0.001447136,"domain_scores_codex":[0.9994234,0.0001525708,0.00004406128,0.0001032836,0.0002409532,0.0000358158],"domain_scores_gemma":[0.9986954,0.0005034318,0.0001670437,0.0002388837,0.0003494636,0.00004580145],"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":[0.0002831836,0.00006439428,0.0004483592,0.0003426975,0.00009181628,0.0002402122,0.0002373335,0.07870931,0.2105284,0.01589897,0.00288491,0.6902704],"study_design_scores_gemma":[0.00003114367,0.000113163,0.0007100161,0.00003014225,0.00005441445,0.0007405099,0.00004445322,0.8100961,0.160308,0.008023863,0.01978176,0.00006632575],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002403343,0.0001590102,0.9965823,0.00004492975,0.00002956964,0.00002124142,0.00001484381,0.0004174447,0.0003273631],"genre_scores_gemma":[0.02449059,0.0002629856,0.9735605,0.00003107854,0.00002432706,0.00004431801,0.00006685498,0.0002747102,0.001244604],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001906133,"threshold_uncertainty_score":0.006376624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216323376578455,"score_gpt":0.3097367375434367,"score_spread":0.2875735037776521,"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."}}