{"id":"W2044093652","doi":"10.1109/isbi.2014.6868055","title":"A preliminary study on the effect of motion correction on HARDI reconstruction","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Calgary; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering","keywords":"Interpolation (computer graphics); Diffusion MRI; Motion (physics); Orientation (vector space); Diffusion; Voxel; Computer vision; Computer science; Artificial intelligence; Volume (thermodynamics); Fiber; Diffusion imaging; Mathematics; Physics; Geometry; Materials science; Magnetic resonance imaging","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":[0.004080474,0.001367905,0.0007318053,0.0006739293,0.0007308818,0.0009487808,0.0007851843,0.001258062,0.003647737],"category_scores_gemma":[0.03575483,0.0003241616,0.0006574089,0.0009186622,0.0006437963,0.0009237015,0.0009213818,0.0007738626,0.000739135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002974717,"about_ca_system_score_gemma":0.0006044466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003352574,"about_ca_topic_score_gemma":0.003572717,"domain_scores_codex":[0.9979802,0.000879293,0.0002207369,0.000333399,0.0004325715,0.0001539006],"domain_scores_gemma":[0.9792165,0.01388887,0.00106324,0.002842348,0.002694417,0.0002947107],"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":[0.007743727,0.0008528951,0.01831464,0.00326154,0.0006476732,0.002125286,0.0009768509,0.1530289,0.3861287,0.003329606,0.005121475,0.4184687],"study_design_scores_gemma":[0.0003722183,0.005214314,0.04176017,0.0006121892,0.00071199,0.004803163,0.0005738733,0.5004355,0.4205303,0.003046076,0.0216539,0.000286215],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6053868,0.00622653,0.3790098,0.001000946,0.0005430956,0.0004879116,0.001497521,0.00204575,0.003801685],"genre_scores_gemma":[0.6811337,0.002200989,0.3101814,0.0003387056,0.0001269334,0.0001709072,0.002283133,0.0008886914,0.002675535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004080474,"threshold_uncertainty_score":0.02157986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03671896397938755,"score_gpt":0.3329350652472624,"score_spread":0.2962161012678748,"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."}}