{"id":"https://openalex.org/W2145100560","doi":"https://doi.org/10.1109/isbi.2004.1398771","title":"Differentiable minimin shape distance for incorporating topological priors in biomedical imaging","display_name":"Differentiable minimin shape distance for incorporating topological priors in biomedical imaging","publication_year":2005,"publication_date":"2005-04-06","ids":{"openalex":"https://openalex.org/W2145100560","doi":"https://doi.org/10.1109/isbi.2004.1398771","mag":"2145100560"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2004.1398771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398771","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","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/A5108423340","display_name":"Yonggang Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yonggang Shi","raw_affiliation_strings":["Information Systems and Sciences Laboratory Electrical and Computer Engineering Department, Boston University, USA","Dept. of Electr. & Comput. Eng., Boston Univ., MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Systems and Sciences Laboratory Electrical and Computer Engineering Department, Boston University, USA","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Boston Univ., MA, USA","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060038714","display_name":"W.C. Karl","orcid":"https://orcid.org/0000-0002-8770-2886"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W.C. Karl","raw_affiliation_strings":["Information Systems and Sciences Laboratory Electrical and Computer Engineering Department, Boston University, USA","Dept. of Electr. & Comput. Eng., Boston Univ., MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Systems and Sciences Laboratory Electrical and Computer Engineering Department, Boston University, USA","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Boston Univ., MA, USA","institution_ids":["https://openalex.org/I111088046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111088046"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1247","last_page":"1250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.993399977684021,"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":0.993399977684021,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9801999926567078,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9726999998092651,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7458294034004211},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.621627688407898},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5645118355751038},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5533883571624756},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5273730754852295},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5037328600883484},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.49222126603126526},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4876154959201813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4719140827655792},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.46581530570983887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4276203215122223},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40073174238204956},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.1396792232990265},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.0899234414100647},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08835497498512268}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7458294034004211},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.621627688407898},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5645118355751038},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5533883571624756},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5273730754852295},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5037328600883484},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.49222126603126526},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4876154959201813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4719140827655792},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.46581530570983887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4276203215122223},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40073174238204956},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.1396792232990265},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0899234414100647},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08835497498512268},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2004.1398771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398771","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1942530554","https://openalex.org/W1991113069","https://openalex.org/W2038952578","https://openalex.org/W2078947454","https://openalex.org/W2104095591","https://openalex.org/W2104358837","https://openalex.org/W2116040950","https://openalex.org/W2139383790","https://openalex.org/W2147484997","https://openalex.org/W2148395215","https://openalex.org/W2167338900","https://openalex.org/W2172167640","https://openalex.org/W3211330693"],"related_works":["https://openalex.org/W2102683994","https://openalex.org/W2786007548","https://openalex.org/W2063813108","https://openalex.org/W2373659438","https://openalex.org/W2162755489","https://openalex.org/W1879755808","https://openalex.org/W2072057318","https://openalex.org/W2164781768","https://openalex.org/W1979702773","https://openalex.org/W2050783914"],"abstract_inverted_index":{"In":[0,46],"the":[1,14,27,30,38,61,92,95,102],"application":[2,93],"of":[3,16,32,40,60,94],"curve":[4,67,87],"evolution":[5,68,88],"and":[6,77],"level":[7],"set":[8],"methods":[9],"to":[10,81,101,107],"biomedical":[11],"image":[12,104,114],"analysis,":[13],"incorporation":[15],"geometric":[17],"priors":[18],"for":[19,112],"isolated":[20],"shapes":[21,42],"has":[22],"been":[23],"proved":[24],"useful.":[25],"On":[26],"other":[28],"hand,":[29],"inclusion":[31],"a":[33,44,51,86],"priori":[34],"topological":[35,62,109],"information":[36,111],"concerning":[37],"relationship":[39],"multiple":[41],"remains":[43],"challenge.":[45],"this":[47,78,83],"paper,":[48],"we":[49],"propose":[50],"differentiable":[52],"minimin":[53],"shape":[54],"distance":[55],"(DMSD)":[56],"that":[57],"is":[58,75],"indicative":[59],"relation":[63],"between":[64],"shapes.":[65],"A":[66],"equation":[69],"based":[70],"on":[71],"its":[72],"first":[73],"variation":[74],"derived":[76],"enables":[79],"us":[80],"incorporate":[82,108],"prior":[84,110],"into":[85],"framework.":[89],"We":[90],"demonstrate":[91],"DMSD":[96],"by":[97],"proposing":[98],"an":[99],"extension":[100],"Chan-Vese":[103],"segmentation":[105,115],"model":[106],"challenging":[113],"tasks.":[116]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
