{"id":"https://openalex.org/W2107175890","doi":"https://doi.org/10.1109/isbi.2010.5490133","title":"Exploiting user labels with generalized distance transforms random field level sets","display_name":"Exploiting user labels with generalized distance transforms random field level sets","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2107175890","doi":"https://doi.org/10.1109/isbi.2010.5490133","mag":"2107175890"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2010.5490133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2010.5490133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","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/A5101289796","display_name":"Yingxuan Zhu","orcid":"https://orcid.org/0009-0000-8697-1948"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]},{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingxuan Zhu","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA","Mitsubishi Electric Research Laboratories, Inc., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]},{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories, Inc., USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091650949","display_name":"Kinh Tieu","orcid":"https://orcid.org/0009-0004-4689-8810"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kinh Tieu","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories, Inc., Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories, Inc., Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.511081,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6512","issue":null,"first_page":"904","last_page":"907"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9980999827384949,"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":0.9980999827384949,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9945999979972839,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9926000237464905,"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/image-segmentation","display_name":"Image segmentation","score":0.6368146538734436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6319493055343628},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6239525675773621},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6101824045181274},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.5801048874855042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5514944791793823},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5388294458389282},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.521589457988739},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47501930594444275},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.46164363622665405},{"id":"https://openalex.org/keywords/random-field","display_name":"Random field","score":0.45742475986480713},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.43893975019454956},{"id":"https://openalex.org/keywords/distance-transform","display_name":"Distance transform","score":0.4205470681190491},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.41606244444847107},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4131927192211151},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33675462007522583},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08832293748855591}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6368146538734436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6319493055343628},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6239525675773621},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6101824045181274},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.5801048874855042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5514944791793823},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5388294458389282},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.521589457988739},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47501930594444275},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.46164363622665405},{"id":"https://openalex.org/C130402806","wikidata":"https://www.wikidata.org/wiki/Q5361768","display_name":"Random field","level":2,"score":0.45742475986480713},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43893975019454956},{"id":"https://openalex.org/C73621898","wikidata":"https://www.wikidata.org/wiki/Q2940504","display_name":"Distance transform","level":3,"score":0.4205470681190491},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.41606244444847107},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4131927192211151},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33675462007522583},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08832293748855591},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2010.5490133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2010.5490133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","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":8,"referenced_works":["https://openalex.org/W1991113069","https://openalex.org/W1999244633","https://openalex.org/W2116040950","https://openalex.org/W2118386984","https://openalex.org/W2134839354","https://openalex.org/W2146976149","https://openalex.org/W2169551590","https://openalex.org/W2309471314"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4205800335","https://openalex.org/W2373659438","https://openalex.org/W2392905701","https://openalex.org/W1879755808","https://openalex.org/W2171653019"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2],"approach":[3],"for":[4],"exploiting":[5],"user":[6,20],"labels":[7,21],"with":[8],"random":[9,52],"field":[10,53],"level":[11,45,54,72],"sets":[12,55],"in":[13,69],"image":[14,29,40],"segmentation.":[15],"A":[16],"sparse":[17],"set":[18,46,73],"of":[19,27],"is":[22,48,58],"propagated":[23],"to":[24,50,60],"the":[25,28,61],"rest":[26],"by":[30],"computing":[31],"a":[32,70,80],"generalized":[33],"distance":[34],"transform":[35],"which":[36],"takes":[37],"into":[38],"account":[39],"intensity":[41],"information.":[42],"The":[43],"region-based":[44],"formulation":[47],"modified":[49],"use":[51],"whose":[56],"range":[57],"restricted":[59],"probability":[62],"values.":[63],"These":[64],"two":[65],"ideas":[66],"are":[67,77],"combined":[68],"single":[71],"functional.":[74],"Improved":[75],"results":[76],"shown":[78],"on":[79],"liver":[81],"segmentation":[82],"task.":[83]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
