{"id":"https://openalex.org/W4410028158","doi":"https://doi.org/10.1016/j.compbiomed.2025.110221","title":"Optimizing stroke lesion segmentation: A dual-approach using Gaussian mixture models and nnU-Net","display_name":"Optimizing stroke lesion segmentation: A dual-approach using Gaussian mixture models and nnU-Net","publication_year":2025,"publication_date":"2025-05-02","ids":{"openalex":"https://openalex.org/W4410028158","doi":"https://doi.org/10.1016/j.compbiomed.2025.110221","pmid":"https://pubmed.ncbi.nlm.nih.gov/40318493"},"language":"en","primary_location":{"id":"doi:10.1016/j.compbiomed.2025.110221","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2025.110221","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.compbiomed.2025.110221","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117411500","display_name":"Adrian Mannel","orcid":null},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Adrian Mannel","raw_affiliation_strings":["Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005219575","display_name":"D. Khunt","orcid":null},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dhaval Khunt","raw_affiliation_strings":["Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; University of Trier, Trier, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; University of Trier, Trier, Germany","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029940972","display_name":"Vaibhav Agrawal","orcid":"https://orcid.org/0000-0003-4726-5682"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Vaibhav Agrawal","raw_affiliation_strings":["Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany"],"affiliations":[{"raw_affiliation_string":"Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117411501","display_name":"Kristin Schelling","orcid":null},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]},{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kristin Schelling","raw_affiliation_strings":["Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany"],"affiliations":[{"raw_affiliation_string":"Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I1325886976","https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043052954","display_name":"Eduardo Calder\u00f3n","orcid":"https://orcid.org/0009-0000-3837-7151"},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Eduardo Calder\u00f3n","raw_affiliation_strings":["Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025657000","display_name":"Christian la Foug\u00e8re","orcid":"https://orcid.org/0000-0001-7519-0417"},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian la Foug\u00e8re","raw_affiliation_strings":["Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Cluster of Excellence iFIT (EXC 2180) 'Image-Guided and Functionally Instructed Tumour Therapies', Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; German Cancer Research Center, German Cancer Consortium DKTK, Partner Site T\u00fcbingen, T\u00fcbingen, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Cluster of Excellence iFIT (EXC 2180) 'Image-Guided and Functionally Instructed Tumour Therapies', Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; German Cancer Research Center, German Cancer Consortium DKTK, Partner Site T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074575317","display_name":"Salvador Castaneda Vega","orcid":"https://orcid.org/0000-0002-0484-9904"},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Salvador Castaneda-Vega","raw_affiliation_strings":["Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany. Electronic address: salvador.castaneda@med.uni-tuebingen.de"],"affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University T\u00fcbingen, T\u00fcbingen, Germany. Electronic address: salvador.castaneda@med.uni-tuebingen.de","institution_ids":["https://openalex.org/I8087733"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5074575317"],"corresponding_institution_ids":["https://openalex.org/I8087733"],"apc_list":{"value":2610,"currency":"USD","value_usd":2610},"apc_paid":{"value":2610,"currency":"USD","value_usd":2610},"fwci":2.6381,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89475095,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"192","issue":"Pt A","first_page":"110221","last_page":"110221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9685999751091003,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9685999751091003,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9524000287055969,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6970646381378174},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.5871362686157227},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5839723348617554},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5300079584121704},{"id":"https://openalex.org/keywords/stroke","display_name":"Stroke (engine)","score":0.49481624364852905},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.47899553179740906},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.4648526906967163},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4366830289363861},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3934935927391052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.368399053812027},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24119722843170166},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.183040052652359},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.08452451229095459}],"concepts":[{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6970646381378174},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.5871362686157227},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5839723348617554},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5300079584121704},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.49481624364852905},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.47899553179740906},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.4648526906967163},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4366830289363861},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3934935927391052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.368399053812027},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24119722843170166},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.183040052652359},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08452451229095459},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020521","descriptor_name":"Stroke","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D020521","descriptor_name":"Stroke","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1016/j.compbiomed.2025.110221","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2025.110221","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},{"id":"pmid:40318493","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40318493","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in biology and medicine","raw_type":null}],"best_oa_location":{"id":"doi:10.1016/j.compbiomed.2025.110221","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2025.110221","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G134512499","display_name":null,"funder_award_id":"472-0-0","funder_id":"https://openalex.org/F4320335385","funder_display_name":"Medizinischen Fakult\u00e4t, Eberhard Karls Universit\u00e4t T\u00fcbingen"}],"funders":[{"id":"https://openalex.org/F4320335385","display_name":"Medizinischen Fakult\u00e4t, Eberhard Karls Universit\u00e4t T\u00fcbingen","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1972168313","https://openalex.org/W1992638640","https://openalex.org/W2038320523","https://openalex.org/W2058784273","https://openalex.org/W2070391970","https://openalex.org/W2072565932","https://openalex.org/W2081246241","https://openalex.org/W2088811746","https://openalex.org/W2103731086","https://openalex.org/W2112505121","https://openalex.org/W2221198671","https://openalex.org/W2495645065","https://openalex.org/W2530382854","https://openalex.org/W2571075903","https://openalex.org/W2582728534","https://openalex.org/W2886990131","https://openalex.org/W2936503027","https://openalex.org/W2966967545","https://openalex.org/W2980397927","https://openalex.org/W2994739006","https://openalex.org/W2999248185","https://openalex.org/W3000921899","https://openalex.org/W3014974815","https://openalex.org/W3029253863","https://openalex.org/W3042519501","https://openalex.org/W3046830682","https://openalex.org/W3112701542","https://openalex.org/W3120608793","https://openalex.org/W3135883537","https://openalex.org/W3136212843","https://openalex.org/W4205204006","https://openalex.org/W4205679663","https://openalex.org/W4206958764","https://openalex.org/W4221034033","https://openalex.org/W4226247843","https://openalex.org/W4285140661","https://openalex.org/W4289489408","https://openalex.org/W4294991405","https://openalex.org/W4295442870","https://openalex.org/W4300672471","https://openalex.org/W4361292114","https://openalex.org/W4379390255","https://openalex.org/W4381586957","https://openalex.org/W4385557907","https://openalex.org/W4385879334","https://openalex.org/W4386065608","https://openalex.org/W4388269674","https://openalex.org/W4392539426","https://openalex.org/W4407085158","https://openalex.org/W6631303128","https://openalex.org/W6632813477","https://openalex.org/W6668004972","https://openalex.org/W6726362721","https://openalex.org/W6732369708","https://openalex.org/W6740220579","https://openalex.org/W6754551840","https://openalex.org/W6770229101","https://openalex.org/W6782070623","https://openalex.org/W6785191678","https://openalex.org/W6801724017","https://openalex.org/W6839505966","https://openalex.org/W6853259325","https://openalex.org/W6855261835","https://openalex.org/W6857509765","https://openalex.org/W6859187796"],"related_works":["https://openalex.org/W2912321008","https://openalex.org/W1998607122","https://openalex.org/W1975321310","https://openalex.org/W2014494654","https://openalex.org/W2324368075","https://openalex.org/W2972124131","https://openalex.org/W338149487","https://openalex.org/W3130349901","https://openalex.org/W4403012196","https://openalex.org/W1578916557"],"abstract_inverted_index":{"Machine":[0],"learning-based":[1],"stroke":[2,121,141],"lesion":[3],"segmentation":[4,35,82,127,153,247,271],"models":[5],"are":[6,28,78],"widely":[7,40,245],"used":[8,41,246],"in":[9,67,89,116,120,214,236],"biomedical":[10,60,167],"imaging,":[11],"but":[12],"their":[13,73,87,114],"ability":[14],"to":[15,112,137,145,199],"detect":[16,138],"treatment":[17],"effects":[18],"remains":[19],"largely":[20],"unexplored.":[21],"Gaussian":[22],"Mixture":[23],"Models":[24],"(GMM)":[25],"and":[26,33,69,100,110,171,189],"nnU-Net":[27,49,111,130,165,181],"among":[29],"the":[30,161,218,255],"most":[31],"prominent":[32],"well-established":[34],"workflows.":[36,173],"GMM":[37,109],"has":[38,50,226],"been":[39,227],"for":[42,46,59,97],"probabilistic":[43,221],"tissue":[44],"classification":[45],"decades,":[47],"while":[48],"established":[51],"itself":[52],"as":[53,261],"a":[54,94,237,262],"leading":[55,144],"deep":[56,224],"learning":[57,225],"framework":[58],"image":[61],"segmentation,":[62],"with":[63,183,201,223],"hundreds":[64],"of":[65,164,220,257],"applications":[66],"preclinical":[68],"clinical":[70,101,172],"research.":[71],"Despite":[72],"widespread":[74],"adoption,":[75],"these":[76],"methods":[77,124,222,248],"typically":[79],"evaluated":[80,180],"using":[81],"metrics":[83],"alone,":[84],"without":[85],"assessing":[86],"reliability":[88],"detecting":[90],"therapy-induced":[91,140],"changes":[92,119],"-":[93],"critical":[95],"factor":[96],"translational":[98],"research":[99],"decision-making.":[102],"In":[103],"this":[104,177,252],"study,":[105],"we":[106,179],"systematically":[107,242],"evaluate":[108],"determine":[113],"effectiveness":[115],"identifying":[117],"therapy-related":[118],"volume.":[122],"Both":[123],"demonstrate":[125,232],"strong":[126],"performance;":[128],"however,":[129],"trained":[131,182],"solely":[132,269],"on":[133,270],"manual":[134],"segmentations":[135],"fails":[136],"significant":[139],"volume":[142],"reductions,":[143],"false":[146],"negative":[147],"study":[148,253],"outcomes":[149],"despite":[150],"achieving":[151],"excellent":[152],"metrics.":[154],"This":[155],"limitation":[156],"is":[157],"particularly":[158],"relevant":[159],"given":[160],"increasing":[162],"integration":[163,219],"into":[166],"research,":[168],"multi-center":[169],"trials":[170],"To":[174],"further":[175],"investigate":[176],"issue,":[178],"GMM-derived":[184],"ground":[185],"truth":[186],"(GT)":[187],"labels":[188],"observed":[190],"that":[191],"it":[192],"more":[193],"accurately":[194],"detected":[195],"therapy":[196,215,250,259],"response":[197],"compared":[198],"training":[200],"Manual-GT.":[202],"These":[203],"results":[204,231],"illustrate":[205],"how":[206],"different":[207],"GT":[208],"definitions":[209],"can":[210],"influence":[211],"model":[212],"performance":[213],"assessment.":[216],"While":[217],"previously":[228],"described,":[229],"our":[230],"its":[233],"practical":[234],"impact":[235],"controlled":[238],"experimental":[239],"setting.":[240],"By":[241],"evaluating":[243],"two":[244],"under":[249],"conditions,":[251],"highlights":[254],"importance":[256],"considering":[258],"detection":[260],"key":[263],"evaluation":[264],"criterion,":[265],"rather":[266],"than":[267],"relying":[268],"accuracy.":[272]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-01-20T17:24:06.736184","created_date":"2025-10-10T00:00:00"}