{"id":"W4412563424","doi":"10.36227/techrxiv.175321702.29643742/v1","title":"Gaussian Splatting-Based Registration for PET Image Correction: A Proof-of-Concept Study","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Particle Physics","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Computer science; Artificial intelligence; Proof of concept; Computer vision; Gaussian; Image (mathematics); Image registration; Computer graphics (images)","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":[0.001424218,0.0006850058,0.0005597128,0.0003575899,0.0001896977,0.0009840862,0.001232444,0.0009379681,0.002509493],"category_scores_gemma":[0.002177128,0.0002883454,0.000482587,0.0003541546,0.0005130781,0.0009924216,0.0007245126,0.0008031815,0.0008496337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003768981,"about_ca_system_score_gemma":0.0007923077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001464988,"about_ca_topic_score_gemma":0.0007668345,"domain_scores_codex":[0.9993047,0.00008229765,0.00002027635,0.00009413371,0.0004471581,0.00005142826],"domain_scores_gemma":[0.9993721,0.0001773568,0.00007835114,0.00009532317,0.0002156022,0.00006122184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005542649,0.0005559506,0.0007203069,0.0007810007,0.0001576977,0.001135386,0.0003348745,0.03452971,0.6842932,0.008236831,0.006556102,0.2621447],"study_design_scores_gemma":[0.0001296163,0.00143981,0.000963788,0.00005272359,0.00006519249,0.002337147,0.00006699087,0.3258678,0.6389164,0.00116317,0.02889398,0.0001033182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07086457,0.002226088,0.9172459,0.0007487069,0.0003258798,0.0004373857,0.0001789752,0.002619094,0.005353299],"genre_scores_gemma":[0.3896822,0.002244397,0.6016541,0.0003494306,0.00009733607,0.0002679247,0.0002956311,0.0005206221,0.00488842],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002509493,"threshold_uncertainty_score":0.008395135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0364165291039752,"score_gpt":0.3730869410784462,"score_spread":0.336670411974471,"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."}}