{"id":"W3047159106","doi":"10.1007/s10278-020-00374-6","title":"The Effect of Registration on Voxel-Wise Tofts Model Parameters and Uncertainties from DCE-MRI of Early-Stage Breast Cancer Patients Using 3DSlicer","year":2020,"lang":"en","type":"article","venue":"Journal of Digital Imaging","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lawson Health Research Institute; Cancer Care Ontario; Western University","funders":"Canadian Institutes of Health Research","keywords":"Voxel; Percentile; Image registration; Mathematics; Breast cancer; Nuclear medicine; Artificial intelligence; Breast MRI; Computer science; Pattern recognition (psychology); Medicine; Statistics; Cancer; Image (mathematics); Mammography","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":[0.00304687,0.0006700404,0.0005739114,0.000646457,0.0003379298,0.001289925,0.000615513,0.0009518294,0.0008487595],"category_scores_gemma":[0.0144541,0.0004712195,0.001023455,0.0006870909,0.0004400822,0.0008951447,0.0007427197,0.0008352029,0.0003286428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003943453,"about_ca_system_score_gemma":0.0009014498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004196071,"about_ca_topic_score_gemma":0.004557903,"domain_scores_codex":[0.9988946,0.0004948729,0.00011329,0.000215978,0.0002089989,0.00007232389],"domain_scores_gemma":[0.9944794,0.004076317,0.0004682293,0.0005564095,0.0003576411,0.00006194432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.009897606,0.0004691281,0.05341566,0.0008514692,0.001159706,0.0007111402,0.001238019,0.5476148,0.1362099,0.002026027,0.001387974,0.2450186],"study_design_scores_gemma":[0.0001019173,0.000963315,0.06335662,0.00008713609,0.001030113,0.001431969,0.0003546597,0.7449295,0.1817439,0.002204171,0.003576746,0.0002199292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8554186,0.0017011,0.1376271,0.000309034,0.0001257665,0.00006792805,0.0009861118,0.002419274,0.001345135],"genre_scores_gemma":[0.9737188,0.0003101237,0.02366711,0.00005902298,0.0000158606,0.00003081677,0.0009880716,0.0007377546,0.0004724206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004196071,"threshold_uncertainty_score":0.01611358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02352178559789811,"score_gpt":0.2919689307172624,"score_spread":0.2684471451193643,"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."}}