{"id":"https://openalex.org/W3075027346","doi":"https://doi.org/10.1145/3388770.3407440","title":"ICF: A Shape-based 3D Segmentation Method","display_name":"ICF: A Shape-based 3D Segmentation Method","publication_year":2020,"publication_date":"2020-08-15","ids":{"openalex":"https://openalex.org/W3075027346","doi":"https://doi.org/10.1145/3388770.3407440","mag":"3075027346"},"language":"en","primary_location":{"id":"doi:10.1145/3388770.3407440","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388770.3407440","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGGRAPH 2020 Posters","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/A5111911034","display_name":"Koji Kobayashi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Koji Kobayashi","raw_affiliation_strings":["Vocsis Corporation"],"affiliations":[{"raw_affiliation_string":"Vocsis Corporation","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038154559","display_name":"Koichi Ito","orcid":"https://orcid.org/0000-0001-7431-7105"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koichi Ito","raw_affiliation_strings":["Tohoku University"],"affiliations":[{"raw_affiliation_string":"Tohoku University","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037666211","display_name":"Takafumi Aoki","orcid":"https://orcid.org/0000-0001-8308-2416"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takafumi Aoki","raw_affiliation_strings":["Tohuku University"],"affiliations":[{"raw_affiliation_string":"Tohuku University","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111911034"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08526585,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T12923","display_name":"Digital Image Processing Techniques","score":0.9995999932289124,"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":0.9929999709129333,"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/voxel","display_name":"Voxel","score":0.8551589250564575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5755353569984436},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5691231489181519},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.5539568066596985},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5142332911491394},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.510104238986969},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4727633595466614},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4507831633090973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44974449276924133},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.41129744052886963},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32790452241897583},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.3265710771083832},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21903133392333984},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.11188244819641113},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08255773782730103}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.8551589250564575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5755353569984436},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5691231489181519},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.5539568066596985},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5142332911491394},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.510104238986969},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4727633595466614},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4507831633090973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44974449276924133},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.41129744052886963},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32790452241897583},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.3265710771083832},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21903133392333984},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.11188244819641113},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08255773782730103},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3388770.3407440","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388770.3407440","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGGRAPH 2020 Posters","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":1,"referenced_works":["https://openalex.org/W2078059979"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2892386716","https://openalex.org/W1998563493","https://openalex.org/W4306164210","https://openalex.org/W4313316311","https://openalex.org/W1989570877","https://openalex.org/W1966577812","https://openalex.org/W1522196789"],"abstract_inverted_index":{"As":[0,111],"a":[1,19,33,43,52,61,67,74,87,91,128],"new":[2],"method":[3],"that":[4,38,65],"can":[5,120,151],"contribute":[6],"to":[7,83,95,104,116,140],"3D":[8,20,100,129,148],"shape":[9,145],"analysis,":[10],"we":[11],"propose":[12],"Incremental":[13],"Contour":[14],"Flow":[15],"(ICF),":[16],"which":[17],"divides":[18],"object":[21,130],"into":[22],"segments":[23,107],"separated":[24],"by":[25,78,143],"boundary":[26,125],"surfaces":[27,126],"at":[28],"narrow":[29,53],"parts.":[30],"ICF":[31,119,150],"utilizes":[32],"property":[34],"of":[35,45,56,90],"distance":[36,81],"transform":[37],"generates":[39,121],"local":[40,62],"maxima":[41],"in":[42,51,73,86,113,146,154],"center":[44],"swollen":[46],"part":[47],"and":[48],"bottleneck-like":[49],"structures":[50],"part.":[54],"Core":[55],"segment":[57],"is":[58],"defined":[59],"as":[60,105,108],"maximum":[63],"layer":[64,75,89],"has":[66],"higher":[68],"value":[69],"than":[70],"surrounding":[71,88],"layers":[72],"structure":[76],"generated":[77],"converting":[79],"the":[80,96,109,155],"values":[82],"integers.":[84],"Voxels":[85],"core":[92,97],"are":[93,102],"added":[94],"incrementally,":[98],"thereby":[99],"voxels":[101],"grouped":[103],"many":[106],"cores.":[110],"shown":[112],"an":[114],"example":[115],"be":[117,141,152],"discussed,":[118],"combined":[122],"soap":[123],"bubble-like":[124],"from":[127,132],"made":[131],"merged":[133],"three":[134],"spheres.":[135],"Since":[136],"human":[137],"organs":[138],"tend":[139],"distinguished":[142],"its":[144],"medical":[147,156],"images,":[149],"useful":[153],"imaging":[157],"applications.":[158]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}