{"id":"https://openalex.org/W73004335","doi":null,"title":"Segmenting cortical structures by globally minimal surfaces","display_name":"Segmenting cortical structures by globally minimal surfaces","publication_year":2005,"publication_date":"2005-01-01","ids":{"openalex":"https://openalex.org/W73004335","mag":"73004335"},"language":"en","primary_location":{"id":"mag:73004335","doi":null,"is_oa":false,"landing_page_url":"https://espace.library.uq.edu.au/view/UQ:9735/brainseg.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112992086","display_name":"Ben Appleton","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ben Appleton","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032727499","display_name":"David H. McKinnon","orcid":"https://orcid.org/0000-0001-9549-9921","observed_orcids":["https://orcid.org/0000-0001-9549-9921"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David McKinnon","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9549-9921","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5012379451","display_name":"D. Wang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D. Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01341128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"169","last_page":"174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":1.0,"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":1.0,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/3d-image-segmentation","display_name":"3D image segmentation","score":0.9520000219345093},{"id":"https://openalex.org/keywords/brain-structure-segmentation","display_name":"brain structure segmentation","score":0.6759999990463257},{"id":"https://openalex.org/keywords/maximum-flow","display_name":"maximum flow","score":0.7049999833106995},{"id":"https://openalex.org/keywords/elderly-patients","display_name":"elderly patients","score":0.9539999961853027},{"id":"https://openalex.org/keywords/variational-segmentation","display_name":"variational segmentation","score":0.5789999961853027},{"id":"https://openalex.org/keywords/local-optima-avoidance","display_name":"local optima avoidance","score":0.7419999837875366}],"concepts":[{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.7671056389808655},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7559661269187927},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.6667907238006592},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5396881103515625},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5350936651229858},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.5290882587432861},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.510123074054718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.492424339056015},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43811482191085815},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.42314398288726807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36341410875320435},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3332372307777405},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09597659111022949},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06799402832984924},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:73004335","doi":null,"is_oa":false,"landing_page_url":"https://espace.library.uq.edu.au/view/UQ:9735/brainseg.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1576499941","https://openalex.org/W1989175405","https://openalex.org/W1999601856","https://openalex.org/W2105868963","https://openalex.org/W2112058288","https://openalex.org/W2125430522","https://openalex.org/W2132513126","https://openalex.org/W2133216625","https://openalex.org/W2151783599","https://openalex.org/W3211330693"],"related_works":["https://openalex.org/W7098955092","https://openalex.org/W2072490343","https://openalex.org/W7098017839","https://openalex.org/W1597117521","https://openalex.org/W7099798770","https://openalex.org/W7099011540","https://openalex.org/W1505861171","https://openalex.org/W2105868963","https://openalex.org/W2618631269","https://openalex.org/W7056858256"],"abstract_inverted_index":{"In":[0],"this":[1,108],"paper":[2],"we":[3],"examine":[4],"a":[5,33,56,79,99,126],"new":[6,109],"prospect":[7],"for":[8],"volumetric":[9],"image":[10],"segmentation,":[11],"the":[12,25,71,84,93,96,136],"globally":[13,47,74,139],"minimal":[14,28,48,75,140],"surface":[15,29,49],"algorithm,":[16],"and":[17,36,116],"its":[18],"application":[19,72,137],"to":[20,40,65,77,89,113],"segmenting":[21,78],"anatomical":[22],"structures":[23,82],"in":[24,43,83,92,98],"brain.":[26],"Existing":[27],"algorithms":[30],"typically":[31],"use":[32],"variational":[34],"approach":[35,59],"so":[37],"are":[38],"prone":[39],"becoming":[41],"stuck":[42],"local":[44],"minima.":[45],"The":[46,104],"algorithm":[50],"used":[51],"here":[52],"is":[53,111],"based":[54],"on":[55],"maximal":[57],"flow":[58],"which":[60],"has":[61],"been":[62],"mathematically":[63],"proven":[64],"obtain":[66,114],"optimal":[67],"segmentations.":[68],"We":[69,123],"present":[70],"of":[73,81,95,101,129,138],"surfaces":[76],"number":[80],"brain,":[85],"as":[86,88],"well":[87],"tracking":[90],"changes":[91],"shape":[94],"brain":[97],"study":[100],"elderly":[102],"patients.":[103],"results":[105],"demonstrate":[106],"that":[107,125],"method":[110],"able":[112],"robust":[115],"accurate":[117],"segmentations":[118],"with":[119],"little":[120],"user":[121],"interaction.":[122],"conclude":[124],"wide":[127],"range":[128],"medical":[130],"segmentation":[131],"problems":[132],"may":[133],"benefit":[134],"from":[135],"surfaces.":[141]},"counts_by_year":[],"updated_date":"2026-09-22T06:50:58.402377","created_date":"2016-06-24T00:00:00"}