{"id":"https://openalex.org/W4221151293","doi":"https://doi.org/10.1137/21m1444874","title":"Image Segmentation with Adaptive Spatial Priors from Joint Registration","display_name":"Image Segmentation with Adaptive Spatial Priors from Joint Registration","publication_year":2022,"publication_date":"2022-08-11","ids":{"openalex":"https://openalex.org/W4221151293","doi":"https://doi.org/10.1137/21m1444874"},"language":"en","primary_location":{"id":"doi:10.1137/21m1444874","is_oa":false,"landing_page_url":"https://doi.org/10.1137/21m1444874","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-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/A5038977421","display_name":"Haifeng Li","orcid":"https://orcid.org/0000-0003-1597-3684"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haifeng Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101773276","display_name":"Weihong Guo","orcid":"https://orcid.org/0000-0001-5796-3527"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weihong Guo","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-5796-3527","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361699","display_name":"Jun Liu","orcid":"https://orcid.org/0000-0001-8697-3089"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100360618","display_name":"Li Cui","orcid":"https://orcid.org/0000-0002-7253-1391"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Cui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5108518417","display_name":"Dongxing Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongxing Xie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5873,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.64766918,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"15","issue":"3","first_page":"1314","last_page":"1344"},"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7687411308288574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.724145233631134},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6487597823143005},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.6289132237434387},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5848101377487183},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5757317543029785},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.5521959066390991},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5128772258758545},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.5032047629356384},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4758712351322174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4639309048652649},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16030311584472656},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.13336077332496643}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7687411308288574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.724145233631134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6487597823143005},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.6289132237434387},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5848101377487183},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5757317543029785},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.5521959066390991},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5128772258758545},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.5032047629356384},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4758712351322174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4639309048652649},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16030311584472656},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.13336077332496643},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/21m1444874","is_oa":false,"landing_page_url":"https://doi.org/10.1137/21m1444874","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W74568156","https://openalex.org/W796515066","https://openalex.org/W1608473481","https://openalex.org/W1986399714","https://openalex.org/W1990804363","https://openalex.org/W2034372240","https://openalex.org/W2037316890","https://openalex.org/W2042226984","https://openalex.org/W2044025718","https://openalex.org/W2066839705","https://openalex.org/W2067418953","https://openalex.org/W2100836571","https://openalex.org/W2103857226","https://openalex.org/W2115167851","https://openalex.org/W2117853077","https://openalex.org/W2125130222","https://openalex.org/W2128506906","https://openalex.org/W2147555557","https://openalex.org/W2163140446","https://openalex.org/W2299211235","https://openalex.org/W2520815785","https://openalex.org/W2586165026","https://openalex.org/W2608853860","https://openalex.org/W2624881194","https://openalex.org/W2754599739","https://openalex.org/W2785493516","https://openalex.org/W2795823403","https://openalex.org/W2796249795","https://openalex.org/W2803323941","https://openalex.org/W2945445966","https://openalex.org/W2950771969","https://openalex.org/W2987132611","https://openalex.org/W2995412459","https://openalex.org/W2997028236","https://openalex.org/W3007952292","https://openalex.org/W3037567190","https://openalex.org/W3112931158","https://openalex.org/W4230920194","https://openalex.org/W4231665431","https://openalex.org/W4236288244","https://openalex.org/W4249648739","https://openalex.org/W4249667877","https://openalex.org/W4296760018","https://openalex.org/W4388297464"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W2371519352","https://openalex.org/W4205800335","https://openalex.org/W2386644571","https://openalex.org/W2551987074","https://openalex.org/W2372421320"],"abstract_inverted_index":{"Image":[0],"segmentation":[1,44,62,74,88,144,159,208],"is":[2,89,147,175],"a":[3,61,78,92,111,116,133,178],"crucial":[4],"but":[5],"challenging":[6],"task":[7],"that":[8,154],"has":[9],"many":[10],"applications.":[11],"In":[12,23],"medical":[13],"imaging,":[14],"for":[15,128,139],"instance,":[16],"intensity":[17,99],"inhomogeneity":[18,100],"and":[19,33,75,101,124,130,136,145,163,195,209,213],"noise":[20],"are":[21,29,35],"common.":[22],"thigh":[24,196],"muscle":[25,49,197],"images,":[26],"different":[27],"muscles":[28],"closely":[30],"packed":[31],"together":[32],"there":[34],"often":[36],"no":[37],"clear":[38],"boundaries":[39],"between":[40,143],"them.":[41],"Intensity":[42],"based":[43,90],"models":[45],"cannot":[46],"separate":[47],"one":[48],"from":[50,68],"another.":[51],"To":[52],"solve":[53],"such":[54],"problems,":[55],"in":[56,77],"this":[57],"work":[58],"we":[59],"present":[60],"model":[63,72,192],"with":[64],"adaptive":[65],"spatial":[66,102],"priors":[67],"joint":[69,173,215],"registration.":[70],"This":[71,172],"combines":[73],"registration":[76,105,129,146,210],"unified":[79],"framework":[80,174],"to":[81,156,184,207],"leverage":[82],"their":[83],"positive":[84],"mutual":[85],"influence.":[86],"The":[87,104,141],"on":[91,193],"modified":[93,117],"Gaussian":[94,134],"mixture":[95],"model,":[96],"which":[97,182],"integrates":[98],"smoothness.":[103],"plays":[106],"the":[107,150,158,203],"role":[108],"of":[109,119],"providing":[110],"shape":[112],"prior.":[113],"We":[114,188],"adopt":[115],"sum":[118],"squared":[120],"difference":[121],"fidelity":[122],"term":[123,127],"Tikhonov":[125],"regularity":[126],"also":[131],"utilize":[132],"pyramid":[135],"parametric":[137],"method":[138],"robustness.":[140],"connection":[142],"guaranteed":[148],"by":[149],"cross":[151],"entropy":[152],"metric":[153],"aims":[155],"make":[157],"map":[160],"(from":[161,166],"segmentation)":[162],"deformed":[164],"atlas":[165],"registration)":[167],"as":[168,170,205],"similar":[169],"possible.":[171],"implemented":[176],"within":[177],"constraint":[179],"optimization":[180],"framework,":[181],"leads":[183],"an":[185],"efficient":[186],"algorithm.":[187],"evaluate":[189],"our":[190],"proposed":[191],"synthetic":[194],"MR":[198],"images.":[199],"Numerical":[200],"results":[201],"show":[202],"improvement":[204],"compared":[206],"performed":[211],"separately":[212],"other":[214],"models.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
