{"id":"https://openalex.org/W2755962443","doi":"https://doi.org/10.1109/icip.2017.8296526","title":"A two-stage minimum spanning tree (MST) based clustering algorithm for 2D deformable registration of time sequenced images","display_name":"A two-stage minimum spanning tree (MST) based clustering algorithm for 2D deformable registration of time sequenced images","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2755962443","doi":"https://doi.org/10.1109/icip.2017.8296526","mag":"2755962443"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5035754194","display_name":"Baidya Nath Saha","orcid":"https://orcid.org/0000-0001-6966-636X"},"institutions":[{"id":"https://openalex.org/I124618812","display_name":"Mathematics Research Center","ror":"https://ror.org/02nhmp827","country_code":"MX","type":"facility","lineage":["https://openalex.org/I124618812"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Baidya Nath Saha","raw_affiliation_strings":["Centro de Investigacion en Matematicas AC, Monterrey, Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centro de Investigacion en Matematicas AC, Monterrey, Mexico","institution_ids":["https://openalex.org/I124618812"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082800075","display_name":"Nilanjan Ray","orcid":"https://orcid.org/0000-0002-7588-5400"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nilanjan Ray","raw_affiliation_strings":["Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052055498","display_name":"Sara McArdle","orcid":"https://orcid.org/0000-0003-3795-3772"},"institutions":[{"id":"https://openalex.org/I1311191458","display_name":"La Jolla Institute for Immunology","ror":"https://ror.org/05vkpd318","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1311191458"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sara McArdle","raw_affiliation_strings":["La Jolla Institute for Allergy & Immunology, La Jolla, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"La Jolla Institute for Allergy & Immunology, La Jolla, CA, USA","institution_ids":["https://openalex.org/I1311191458"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020082525","display_name":"Klaus Ley","orcid":"https://orcid.org/0000-0001-9339-3672"},"institutions":[{"id":"https://openalex.org/I1311191458","display_name":"La Jolla Institute for Immunology","ror":"https://ror.org/05vkpd318","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1311191458"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Klaus Ley","raw_affiliation_strings":["La Jolla Institute for Allergy & Immunology, La Jolla, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"La Jolla Institute for Allergy & Immunology, La Jolla, CA, USA","institution_ids":["https://openalex.org/I1311191458"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10366739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1472","last_page":"1476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9966999888420105,"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":0.9966999888420105,"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":0.9897000193595886,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9832000136375427,"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/minimum-spanning-tree","display_name":"Minimum spanning tree","score":0.8174641132354736},{"id":"https://openalex.org/keywords/spanning-tree","display_name":"Spanning tree","score":0.7581213712692261},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.665615439414978},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.6205041408538818},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6018367409706116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.569568395614624},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.557602047920227},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5171165466308594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5095992088317871},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.49319881200790405},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49063459038734436},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4728788733482361},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4442727863788605},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3851865231990814},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3849785327911377},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07327157258987427}],"concepts":[{"id":"https://openalex.org/C13743678","wikidata":"https://www.wikidata.org/wiki/Q240464","display_name":"Minimum spanning tree","level":2,"score":0.8174641132354736},{"id":"https://openalex.org/C64331007","wikidata":"https://www.wikidata.org/wiki/Q831672","display_name":"Spanning tree","level":2,"score":0.7581213712692261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.665615439414978},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.6205041408538818},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6018367409706116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.569568395614624},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.557602047920227},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5171165466308594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5095992088317871},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.49319881200790405},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49063459038734436},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4728788733482361},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4442727863788605},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3851865231990814},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3849785327911377},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07327157258987427},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.6399999856948853,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1548529611","https://openalex.org/W1975214603","https://openalex.org/W1985406644","https://openalex.org/W1991141821","https://openalex.org/W2016029650","https://openalex.org/W2026140461","https://openalex.org/W2068293605","https://openalex.org/W2071949631","https://openalex.org/W2099540110","https://openalex.org/W2103857226","https://openalex.org/W2107375511","https://openalex.org/W2120967246","https://openalex.org/W2123437836","https://openalex.org/W2124747973","https://openalex.org/W2131938193","https://openalex.org/W2133665775","https://openalex.org/W2412888170","https://openalex.org/W2470229926","https://openalex.org/W2752885492"],"related_works":["https://openalex.org/W2099915933","https://openalex.org/W2418231958","https://openalex.org/W4380840098","https://openalex.org/W3116169590","https://openalex.org/W1703428550","https://openalex.org/W2044443696","https://openalex.org/W2503538928","https://openalex.org/W3101281637","https://openalex.org/W2390742649","https://openalex.org/W1561849181"],"abstract_inverted_index":{"Significant":[0],"cardiac":[1],"and":[2,19,43,141,153,162],"respiratory":[3],"motion":[4],"of":[5,11,17,26,87,103,179,197],"the":[6,15,24,65,73,85,88,91,101,104,113,118,125,128,138,166,176],"living":[7],"subject,":[8],"occasional":[9],"spells":[10],"defocus,":[12],"drifts":[13,161],"in":[14,32,75,127,165],"field":[16],"view,":[18],"long":[20],"image":[21,29,54,67,121,195],"sequences":[22,30,196],"make":[23],"registration":[25,56,108,133,145,157],"in-vivo":[27],"microscopy":[28,194],"used":[31],"atherosclerosis":[33],"study":[34,40],"an":[35],"onerous":[36],"task.":[37],"In":[38],"this":[39],"we":[41],"developed":[42],"implemented":[44],"a":[45,60,77,143],"novel":[46],"Minimum":[47],"Spanning":[48],"Tree":[49],"(MST)-based":[50],"clustering":[51],"method":[52,189],"for":[53,64],"sequence":[55],"that":[57,131],"first":[58],"constructs":[59],"minimum":[61],"spanning":[62,70,92],"tree":[63,71,93],"input":[66],"sequence.":[68,89,168],"The":[69],"re-orders":[72],"images":[74,82,126],"such":[76],"way":[78],"where":[79],"poor":[80],"quality":[81],"appear":[83],"at":[84],"end":[86],"Then":[90],"is":[94,109,134,146],"clustered":[95],"into":[96],"several":[97],"groups":[98],"based":[99],"on":[100,193],"similarity":[102],"images.":[105],"Subsequently":[106],"deformable":[107,144,156],"conducted":[110],"locally":[111],"within":[112],"group":[114],"with":[115],"respect":[116],"to":[117,136,149],"local":[119],"anchor":[120,140],"selected":[122],"automatically":[123],"from":[124,186],"group.":[129],"After":[130],"coarse":[132],"performed":[135,147],"find":[137],"global":[139],"then":[142],"globally":[148],"incorporate":[150],"larger":[151,160],"drift":[152],"distortion.":[154],"Two-stage":[155],"incrementally":[158],"incorporates":[159],"distortions":[163],"present":[164],"longer":[167],"Our":[169,188],"algorithm":[170],"involves":[171],"very":[172],"few":[173],"tuning":[174],"parameters,":[175],"optimal":[177],"value":[178],"these":[180],"parameters":[181],"can":[182],"be":[183],"easily":[184],"learned":[185],"data.":[187],"outperforms":[190],"other":[191],"methods":[192],"mouse":[198],"arteries.":[199]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}