{"doi":"10.1007/978-3-642-22092-0_36","title":"Generalized Partial Volume: An Inferior Density Estimator to Parzen Windows for Normalized Mutual Information","abstract":null,"journal":"Lecture Notes in Computer Science","year":2011,"id":663042,"datarank":0.38474240361923057,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"self_citation_contribution":0.38474240361923057,"citation_network_contribution":0.0,"self_endowment_contribution":0.38474240361923057,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":12,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":753908,"name":"Jon Sporring","orcid":"0000-0003-1261-6702","position":1,"is_corresponding":false},{"id":618396,"name":"Sune Darkner","orcid":"0000-0001-6114-7100","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Generalized Partial Volume: An Inferior Density Estimator to Parzen Windows for Normalized Mutual Information","abstract":"Mutual Information (MI) and normalized mutual information (NMI) are popular choices as similarity measure for multimodal image registration. Presently, one of two approaches is often used for estimating these measures: The Parzen Window (PW) and the Generalized Partial Volume (GPV). Their theoretical relation has so far been unexplored. We present the direct connection between PW and GPV for NMI in the case of rigid and non-rigid image registration. Through step-by-step derivations of PW and GPV we clarify the difference and show that GPV is algorithmically inferior to PW from a model point of view as well as w.r.t. computational complexity. Finally, we present algorithms for both approaches for NMI which is comparable in speed to Sum of Squared Differences (SSD), and we illustrate the differences between PW and GPV on a number of registration examples.","is_dataset_classified":null,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21761676","pmcid":null,"openalex_id":"https://openalex.org/W5924924","authors":[],"funders":[{"funder_name":"Villum Fonden","grant_id":"00008721","title":null}],"total_grants":1,"fwci":1.4258,"citation_percentile":0.8292838,"influential_citations":0,"citation_trend":[{"year":2012,"count":2},{"year":2013,"count":2},{"year":2014,"count":1},{"year":2015,"count":1},{"year":2017,"count":1},{"year":2018,"count":1},{"year":2021,"count":3}],"oa_status":"green","license":"other-oa","oa_locations":[{"url":"https://curis.ku.dk/ws/files/170212449/IPMI_submission_corrected.pdf","host_type":"repository"},{"url":"https://curis.ku.dk/ws/files/170212449/IPMI_submission_corrected.pdf","host_type":"repository"},{"url":"http://link.springer.com/content/pdf/10.1007/978-3-642-22092-0_36","host_type":"publisher"},{"url":"https://curis.ku.dk/portal/da/publications/generalized-partial-volume(169918b1-8d85-4f2c-84de-3f51af9e9f01).html","host_type":"repository"},{"url":"https://doi.org/10.1007/978-3-642-22092-0_36","host_type":"book series"},{"url":"https://pubmed.ncbi.nlm.nih.gov/21761676","host_type":"repository"},{"url":"https://researchprofiles.ku.dk/da/publications/169918b1-8d85-4f2c-84de-3f51af9e9f01","host_type":"repository"}],"fields_of_study":["Medical Image Segmentation Techniques","Advanced Image and Video Retrieval Techniques","Robotics and Sensor-Based Localization","Algorithms","Image Enhancement","Image Interpretation, Computer-Assisted","Magnetic Resonance Imaging","Pattern Recognition, Automated","Reproducibility of Results","Sensitivity and Specificity","Subtraction Technique"],"mesh_terms":["Algorithms","Image Enhancement","Image Interpretation, Computer-Assisted","Magnetic Resonance Imaging","Pattern Recognition, Automated","Sensitivity and Specificity","Subtraction Technique","Reproducibility of Results"],"keywords":["Mutual information","Estimator","Similarity measure","Volume (thermodynamics)","Computer science","Image registration","Similarity (geometry)","Point (geometry)","Image (mathematics)","Artificial intelligence","Window (computing)","Measure (data warehouse)","Mathematics","Algorithm","Relation (database)","Kernel density estimation","Connection (principal bundle)","Kernel (algebra)","Computer vision","Pattern recognition (psychology)","Data mining","Discrete mathematics","Statistics","Geometry"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-12T19:19:06.019091Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}