{"id":"W2128894842","doi":"10.1109/4233.966105","title":"Wavelet-based space-frequency compression of ultrasound images","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Information Technology in Biomedicine","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Set partitioning in hierarchical trees; Computer science; Artificial intelligence; Computer vision; Codec; Wavelet; Image compression; Ultrasound; Wavelet transform; Data compression; Grayscale; Pattern recognition (psychology); Mathematics; Image (mathematics); Image processing; Discrete wavelet transform; Radiology; Medicine","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":[0.000253552,0.0002789576,0.0002369742,0.0008476562,0.0001436749,0.0002823944,0.0002231709,0.0002919793,0.001032991],"category_scores_gemma":[0.001175387,0.0000715632,0.0001800601,0.0007959271,0.0003237697,0.0004141631,0.000201316,0.0002122062,0.0003147469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001413651,"about_ca_system_score_gemma":0.0001400875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006048857,"about_ca_topic_score_gemma":0.0006678498,"domain_scores_codex":[0.9998105,0.00002818599,0.000009967956,0.00001515185,0.0001237984,0.00001235191],"domain_scores_gemma":[0.9997463,0.0001215315,0.00001780936,0.00003896427,0.00006898811,0.000006439416],"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":[0.0002938955,0.00005012897,0.0006012995,0.0002546637,0.00002047506,0.0002893725,0.0001747598,0.04601489,0.2619984,0.010741,0.001763587,0.6777976],"study_design_scores_gemma":[0.00003542287,0.0004795117,0.004175648,0.00006099051,0.00004537226,0.002078822,0.00009367789,0.5965614,0.3694833,0.006949935,0.01998524,0.00005075684],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1379204,0.001932477,0.8536896,0.0002698427,0.0001827966,0.0001226163,0.0001597628,0.0007378929,0.004984639],"genre_scores_gemma":[0.4773045,0.002650777,0.5150725,0.0001317383,0.0001899953,0.00009351027,0.0003603404,0.00009995058,0.004096695],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001032991,"threshold_uncertainty_score":0.003455639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008296223714880096,"score_gpt":0.2590608214615913,"score_spread":0.2507645977467112,"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."}}