{"id":"https://openalex.org/W2219958065","doi":"https://doi.org/10.1109/spa.2015.7365110","title":"A centerline-based algorithm for estimation of blood vessels radii from 3D raster images","display_name":"A centerline-based algorithm for estimation of blood vessels radii from 3D raster images","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2219958065","doi":"https://doi.org/10.1109/spa.2015.7365110","mag":"2219958065"},"language":"en","primary_location":{"id":"doi:10.1109/spa.2015.7365110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spa.2015.7365110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5091913767","display_name":"Jacek Blumenfeld","orcid":null},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jacek Blumenfeld","raw_affiliation_strings":["Institute of Electronics, Lodz University of Technology, Lodz, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics, Lodz University of Technology, Lodz, Poland","institution_ids":["https://openalex.org/I188884621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030949883","display_name":"Marek Koci\u0144ski","orcid":"https://orcid.org/0000-0001-7088-4823"},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Marek Kocinski","raw_affiliation_strings":["Institute of Electronics, Lodz University of Technology, Lodz, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics, Lodz University of Technology, Lodz, Poland","institution_ids":["https://openalex.org/I188884621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062964220","display_name":"Andrzej Materka","orcid":"https://orcid.org/0000-0003-0864-1518"},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Andrzej Materka","raw_affiliation_strings":["Institute of Electronics, Lodz University of Technology, Lodz, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics, Lodz University of Technology, Lodz, Poland","institution_ids":["https://openalex.org/I188884621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9361,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.82944477,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"34","issue":null,"first_page":"38","last_page":"43"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T10816","display_name":"Cerebrovascular and Carotid Artery Diseases","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.8428860306739807},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5584417581558228},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5258496403694153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49572694301605225},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4770302474498749},{"id":"https://openalex.org/keywords/tangent","display_name":"Tangent","score":0.4292669892311096},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41604113578796387},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3544490337371826},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.34783345460891724},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2238348424434662}],"concepts":[{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.8428860306739807},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5584417581558228},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5258496403694153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49572694301605225},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4770302474498749},{"id":"https://openalex.org/C138187205","wikidata":"https://www.wikidata.org/wiki/Q131251","display_name":"Tangent","level":2,"score":0.4292669892311096},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41604113578796387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3544490337371826},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.34783345460891724},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2238348424434662},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spa.2015.7365110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spa.2015.7365110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W428152886","https://openalex.org/W1540289445","https://openalex.org/W1590281895","https://openalex.org/W1940429402","https://openalex.org/W2052644075","https://openalex.org/W2063396027","https://openalex.org/W2105845027","https://openalex.org/W2109200236","https://openalex.org/W2115363972","https://openalex.org/W2129534965","https://openalex.org/W2146564473","https://openalex.org/W2152374117","https://openalex.org/W2168005337","https://openalex.org/W2464090906","https://openalex.org/W4235770099"],"related_works":["https://openalex.org/W2611031068","https://openalex.org/W1704347466","https://openalex.org/W1996936972","https://openalex.org/W4283017538","https://openalex.org/W1545275724","https://openalex.org/W2802707792","https://openalex.org/W2569979269","https://openalex.org/W2075777916","https://openalex.org/W3021699548","https://openalex.org/W4291718021"],"abstract_inverted_index":{"Two":[0],"approaches":[1],"to":[2,50,61,75,113,160],"Hessian-based":[3],"estimation":[4],"of":[5,35,93,125,141,172,178],"tubular":[6,25],"blood-vessel":[7],"radius":[8,90,118],"from":[9],"3D":[10,43],"raster":[11],"images":[12,183],"are":[13,39],"compared.":[14],"In":[15,97],"the":[16,30,36,62,76,94,98,101,108,114,126,150,168,173],"proposed":[17,66,169],"approach,":[18],"binary":[19,37],"skeleton":[20,38,84],"is":[21,71,91,105,119,153,165,184],"found":[22],"for":[23,167,176],"each":[24,83],"vessel-tree":[26],"branch":[27],"by":[28,79,107,132,137],"thresholding":[29],"Hessian-derived":[31],"vesselness":[32],"image.":[33],"Coordinates":[34],"approximated":[40],"with":[41,48],"smooth":[42],"spline":[44],"functions.":[45],"Their":[46],"derivatives":[47],"respect":[49],"arc":[51],"length":[52],"give":[53],"local":[54,89,109],"tangent":[55],"vectors,":[56],"and":[57,146,158,163],"thus":[58],"planes":[59],"normal":[60],"vessel":[63,77,88,102,127],"centerline.":[64],"A":[65],"image":[67,161],"intensity":[68],"profile":[69],"model":[70,95],"then":[72],"least-squares":[73],"fitted":[74],"cross-section":[78,128],"those":[80],"planes,":[81],"at":[82],"point.":[85],"The":[86,117,139],"circular":[87],"one":[92],"parameters.":[96],"reference":[99],"method,":[100],"centerline":[103],"direction":[104],"defined":[106],"Hessian":[110,143],"eigenvector":[111],"corresponding":[112],"smallest":[115],"eigenvalue.":[116],"estimated":[120],"using":[121],"a":[122],"square":[123],"root":[124],"area":[129],"(as":[130],"obtained":[131],"an":[133],"adaptive":[134],"thresholding),":[135],"divided":[136],"\u03c0.":[138],"impact":[140],"Frangi":[142],"filter":[144],"parameters":[145],"scale":[147],"selection":[148],"on":[149],"methods'":[151],"performance":[152],"examined.":[154],"Higher":[155],"accuracy,":[156],"precision":[157],"robustness":[159],"noise":[162],"artifacts":[164],"demonstrated":[166],"method.":[170],"Example":[171],"method":[174],"suitability":[175],"modeling":[177],"brain":[179],"vasculature":[180],"magnetic":[181],"resonance":[182],"also":[185],"presented":[186],"in":[187],"this":[188],"paper.":[189]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
