{"id":"W4393154023","doi":"10.1609/aaai.v38i6.28418","title":"MedSegDiff-V2: Diffusion-Based Medical Image Segmentation with Transformer","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":235,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Segmentation; Image segmentation","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":[0.001500303,0.001039225,0.0009091932,0.001372111,0.0004314402,0.001491534,0.002929462,0.00217103,0.005109677],"category_scores_gemma":[0.003955434,0.0007024297,0.001407966,0.0008987517,0.0006304201,0.001442456,0.002305384,0.001792724,0.002079256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134529,"about_ca_system_score_gemma":0.001732105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005665289,"about_ca_topic_score_gemma":0.008247607,"domain_scores_codex":[0.9995872,0.0000805618,0.00003073041,0.0001139091,0.0001458954,0.00004170779],"domain_scores_gemma":[0.999492,0.0002105457,0.0000429305,0.0001056312,0.0000985713,0.00005034895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005682598,0.0002065967,0.002090845,0.0006054998,0.000357958,0.0003393244,0.0002500936,0.2419845,0.04078941,0.0303754,0.03673751,0.6456947],"study_design_scores_gemma":[0.00006096221,0.00007000653,0.000198233,0.00001799002,0.00002243171,0.0003499135,0.00001803582,0.9684916,0.01219889,0.01145213,0.007090847,0.00002902978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006167725,0.0005377449,0.9761651,0.0003943421,0.00009940879,0.0001398156,0.0005432381,0.01436291,0.001589778],"genre_scores_gemma":[0.1540539,0.0006378616,0.8342901,0.0007595047,0.00008833668,0.0002649631,0.002385071,0.003184782,0.004335459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005665289,"threshold_uncertainty_score":0.01709354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0632182676501923,"score_gpt":0.3097150635355869,"score_spread":0.2464967958853946,"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."}}