{"id":"https://openalex.org/W2196711271","doi":"https://doi.org/10.1109/ipta.2015.7367089","title":"Coverage segmentation of 3D thin structures","display_name":"Coverage segmentation of 3D thin structures","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2196711271","doi":"https://doi.org/10.1109/ipta.2015.7367089","mag":"2196711271"},"language":"en","primary_location":{"id":"doi:10.1109/ipta.2015.7367089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2015.7367089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5066406673","display_name":"Krist\u00edna Lidayov\u00e1","orcid":null},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Kristina Lidayova","raw_affiliation_strings":["Division of Visual Information and Interaction, Uppsala University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Visual Information and Interaction, Uppsala University, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009537079","display_name":"Joakim Lindblad","orcid":"https://orcid.org/0000-0001-7312-8222"},"institutions":[{"id":"https://openalex.org/I170726198","display_name":"University of Novi Sad","ror":"https://ror.org/00xa57a59","country_code":"RS","type":"education","lineage":["https://openalex.org/I170726198"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Joakim Lindblad","raw_affiliation_strings":["Faculty of Technical Sciences, University of Novi Sad, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Technical Sciences, University of Novi Sad, Serbia","institution_ids":["https://openalex.org/I170726198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024324589","display_name":"Nata\u0161a Sladoje","orcid":"https://orcid.org/0000-0002-6041-6310"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]},{"id":"https://openalex.org/I1338511612","display_name":"Serbian Academy of Sciences and Arts","ror":"https://ror.org/05m1y4204","country_code":"RS","type":"government","lineage":["https://openalex.org/I1338511612"]}],"countries":["RS","SE"],"is_corresponding":false,"raw_author_name":"Natasa Sladoje","raw_affiliation_strings":["Division of Visual Information and Interaction, Uppsala University, Sweden","Mathematical Institutte, Serbian Academy of Sciences and Arts, Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Visual Information and Interaction, Uppsala University, Sweden","institution_ids":["https://openalex.org/I123387679"]},{"raw_affiliation_string":"Mathematical Institutte, Serbian Academy of Sciences and Arts, Serbia","institution_ids":["https://openalex.org/I1338511612"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017062028","display_name":"Hans Frimmel","orcid":null},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Hans Frimmel","raw_affiliation_strings":["Division of Scientific Computing, Uppsala University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Scientific Computing, Uppsala University, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109538889","display_name":"Chunliang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Chunliang Wang","raw_affiliation_strings":["School of Technology and Health, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Technology and Health, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084226420","display_name":"\u00d6rjan Smedby","orcid":"https://orcid.org/0000-0002-7750-1917"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Orjan Smedby","raw_affiliation_strings":["School of Technology and Health, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Technology and Health, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"23","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9983999729156494,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/segmentation","display_name":"Segmentation","score":0.8263988494873047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.773723840713501},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7533587217330933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6867478489875793},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6615164279937744},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.6502490639686584},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6157715320587158},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5971289277076721},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4871661365032196},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43156641721725464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3445974588394165},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22363463044166565}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8263988494873047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.773723840713501},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7533587217330933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6867478489875793},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6615164279937744},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.6502490639686584},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6157715320587158},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5971289277076721},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4871661365032196},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43156641721725464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3445974588394165},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22363463044166565},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipta.2015.7367089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2015.7367089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Image Processing Theory, Tools and Applications (IPTA)","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":11,"referenced_works":["https://openalex.org/W98223200","https://openalex.org/W1497510501","https://openalex.org/W1502252694","https://openalex.org/W1593865632","https://openalex.org/W2049429038","https://openalex.org/W2070515158","https://openalex.org/W2101524669","https://openalex.org/W2148223612","https://openalex.org/W2161557710","https://openalex.org/W6603885426","https://openalex.org/W6635413808"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W1986655823","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W4205800335","https://openalex.org/W2055202857","https://openalex.org/W2371519352","https://openalex.org/W2386644571","https://openalex.org/W2372421320"],"abstract_inverted_index":{"We":[0,29],"present":[1],"a":[2,54,73,86,92],"coverage":[3,22,93],"segmentation":[4,23,57,70,94],"method":[5,15,24,46,52],"for":[6,25],"extracting":[7],"thin":[8,27],"structures":[9],"in":[10,119,121],"three-dimensional":[11],"images.":[12],"The":[13,51],"proposed":[14,110],"is":[16],"an":[17,59],"improved":[18],"extension":[19],"of":[20,44,77,108,123],"our":[21],"2D":[26],"structures.":[28],"suggest":[30],"implementation":[31],"that":[32,42],"enables":[33],"low":[34],"memory":[35],"consumption":[36],"and":[37,40,61,67,102,115],"processing":[38],"time,":[39],"by":[41],"applicability":[43],"the":[45,68,78,96,109],"on":[47,113,116],"real":[48,117],"CTA":[49],"data.":[50],"needs":[53],"reliable":[55],"crisp":[56,69,75],"as":[58,85],"input":[60],"uses":[62],"information":[63],"from":[64],"linear":[65],"unmixing":[66],"to":[71,91,125],"create":[72],"high-resolution":[74],"reconstruction":[76],"object,":[79],"which":[80],"can":[81],"then":[82],"be":[83],"used":[84],"final":[87],"result,":[88],"or":[89],"down-sampled":[90],"at":[95],"starting":[97],"image":[98],"resolution.":[99],"Performed":[100],"quantitative":[101],"qualitative":[103],"analysis":[104],"confirm":[105],"excellent":[106],"performance":[107],"method,":[111],"both":[112],"synthetic":[114],"data,":[118],"particular":[120],"terms":[122],"robustness":[124],"noise.":[126]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
