{"id":"W2954571431","doi":"10.22215/etd/2019-13528","title":"Impact of Pinhole Collimation on SPECT Image Quality Metrics, and Methods for Patient-Specific Assessment of Noise and Standardization of Imaging Protocols","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"University of Ottawa; Society of Nuclear Medicine and Molecular Imaging","keywords":"Noise (video); Artificial intelligence; Image noise; Computer science; Computer vision; Image resolution; Pinhole (optics); Image quality; Voxel; Orientation (vector space); Correction for attenuation; Attenuation; Mathematics; Image (mathematics); Physics; Optics","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":[0.01829842,0.0008549128,0.0007097134,0.0009115725,0.0004330013,0.002237721,0.0008559537,0.0008733411,0.001397616],"category_scores_gemma":[0.07069863,0.000684474,0.0003692617,0.00114939,0.0005714804,0.001029001,0.0009238018,0.0007869026,0.0002814582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101272,"about_ca_system_score_gemma":0.00131914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001449219,"about_ca_topic_score_gemma":0.002091487,"domain_scores_codex":[0.987895,0.00592945,0.00106214,0.001328871,0.003603099,0.0001815132],"domain_scores_gemma":[0.9583209,0.02905664,0.004932991,0.002918531,0.004457409,0.0003134314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004682146,0.000329102,0.05091665,0.003759645,0.000678562,0.0004996565,0.001708698,0.04058236,0.3119932,0.008227622,0.005430068,0.5711923],"study_design_scores_gemma":[0.000479168,0.004995317,0.229644,0.001177723,0.001245673,0.00555257,0.0008403207,0.2281466,0.4770358,0.008317993,0.04199857,0.0005662825],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1400507,0.007152393,0.8454059,0.0006574073,0.0002337992,0.0009981217,0.0006904042,0.002025057,0.00278613],"genre_scores_gemma":[0.3785835,0.002645845,0.6134481,0.0004054278,0.00007864023,0.001332494,0.0008573564,0.001431189,0.001217452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01829842,"threshold_uncertainty_score":0.09677243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04706969171909929,"score_gpt":0.5292805084881724,"score_spread":0.4822108167690731,"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."}}