{"id":"https://openalex.org/W2997312995","doi":"https://doi.org/10.1145/3364836.3364874","title":"Application of Distance Regularized Chan-Vese Method for Kidney Segmentation in Renal Scintigraphy","display_name":"Application of Distance Regularized Chan-Vese Method for Kidney Segmentation in Renal Scintigraphy","publication_year":2019,"publication_date":"2019-08-24","ids":{"openalex":"https://openalex.org/W2997312995","doi":"https://doi.org/10.1145/3364836.3364874","mag":"2997312995"},"language":"en","primary_location":{"id":"doi:10.1145/3364836.3364874","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3364836.3364874","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third International Symposium on Image Computing and Digital Medicine","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/A5100677700","display_name":"Miao Li","orcid":"https://orcid.org/0000-0001-6196-2041"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miao Li","raw_affiliation_strings":["Sichuan University, College of Electrical Engineering, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University, College of Electrical Engineering, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027160643","display_name":"Xiujuan Zheng","orcid":"https://orcid.org/0000-0002-4703-9530"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiujuan Zheng","raw_affiliation_strings":["Sichuan University, College of Electrical Engineering, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University, College of Electrical Engineering, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100399921","display_name":"Kai Liu","orcid":"https://orcid.org/0000-0002-6433-6529"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Liu","raw_affiliation_strings":["Sichuan University, College of Electrical Engineering, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University, College of Electrical Engineering, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.4887,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63162524,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"192","last_page":"196"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11174","display_name":"Pediatric Urology and Nephrology Studies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T11885","display_name":"MRI in cancer diagnosis","score":0.9954000115394592,"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/region-of-interest","display_name":"Region of interest","score":0.7677053213119507},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7032619714736938},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7026707530021667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6570757031440735},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4807679355144501},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4508587121963501},{"id":"https://openalex.org/keywords/renal-function","display_name":"Renal function","score":0.41979682445526123},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34780555963516235},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17999643087387085}],"concepts":[{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.7677053213119507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7032619714736938},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7026707530021667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6570757031440735},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4807679355144501},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4508587121963501},{"id":"https://openalex.org/C159641895","wikidata":"https://www.wikidata.org/wiki/Q108377937","display_name":"Renal function","level":2,"score":0.41979682445526123},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34780555963516235},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17999643087387085},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3364836.3364874","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3364836.3364874","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third International Symposium on Image Computing and Digital Medicine","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1965007014","https://openalex.org/W1979393293","https://openalex.org/W1988111033","https://openalex.org/W2006090662","https://openalex.org/W2029751032","https://openalex.org/W2095049733","https://openalex.org/W2113745526","https://openalex.org/W2116040950","https://openalex.org/W2122184585","https://openalex.org/W2154153553","https://openalex.org/W2257883463","https://openalex.org/W2324419763","https://openalex.org/W2597507805","https://openalex.org/W2605795864","https://openalex.org/W2794831444","https://openalex.org/W2808552700","https://openalex.org/W4248718655"],"related_works":["https://openalex.org/W2783512720","https://openalex.org/W2076032188","https://openalex.org/W2083366373","https://openalex.org/W2964546465","https://openalex.org/W2373938009","https://openalex.org/W135926036","https://openalex.org/W2099961086","https://openalex.org/W2128742127","https://openalex.org/W2086703795","https://openalex.org/W1522196789"],"abstract_inverted_index":{"The":[0,81,196,213],"glomerular":[1],"filtration":[2],"rate":[3],"(GFR)":[4],"is":[5,19,51,84,132,244],"a":[6,99,225,245],"crucial":[7],"index":[8],"to":[9,22,26,47,53,78,134,145,153,228,248],"measure":[10,250],"renal":[11,28,65,174,210],"function.":[12],"In":[13,68,163],"clinical":[14,69,79,164,217],"practice,":[15],"the":[16,31,44,55,61,71,92,109,112,118,122,136,147,155,159,166,185,189,216,221,251],"Gates":[17,45],"method":[18,46,106,131,187,223,243,247],"often":[20,74],"used":[21],"obtain":[23,91,229],"GFR":[24,208,231,252],"and":[25,39,87,116,152],"evaluate":[27],"function,":[29],"but":[30],"results":[32,197,214],"are":[33,73],"easily":[34],"affected":[35],"by":[36,139,194],"image":[37],"quality":[38],"physicians'":[40],"experience.":[41,80],"When":[42],"using":[43],"calculate":[48],"GFR,":[49],"it":[50],"required":[52],"delineate":[54],"region":[56],"of":[57,60,94,111,124,149,168,192,215,253],"interest":[58],"(ROI)":[59],"kidney":[62,95],"in":[63,121,142,158,205,209],"dynamic":[64,175,211],"scintigraphy":[66],"firstly.":[67],"environment,":[70],"ROIs":[72],"delineated":[75],"manually":[76],"according":[77],"manual":[82,140,234],"process":[83,123],"subjective,":[85],"complicated":[86],"low":[88],"repeatable.":[89],"To":[90],"ROI":[93,129,143,150,182,241],"accurately,":[96],"we":[97],"propose":[98],"distance":[100,114],"regularization":[101],"Chan-Vese":[102],"(DRCV)":[103],"method.":[104],"This":[105,126],"effectively":[107],"restrains":[108],"degradation":[110],"symbol":[113],"function":[115],"reduces":[117,188],"computational":[119,190],"complexity":[120],"segmentation.":[125],"fully":[127],"automated":[128,240],"extraction":[130,183],"proposed":[133,186,222],"avoid":[135],"errors":[137],"caused":[138],"intervention":[141],"mapping,":[144],"improve":[146],"accuracy":[148],"extraction,":[151],"reduce":[154],"time":[156,191],"consumed":[157],"whole":[160],"detection":[161,242],"process.":[162],"experiments,":[165],"data":[167],"213":[169],"subjects":[170],"who":[171],"underwent":[172],"99mTc-DTPA":[173],"imaging":[176],"were":[177],"analyzed.":[178],"Compared":[179],"with":[180,255],"previous":[181],"methods,":[184],"segmentation":[193],"30%.":[195],"show":[198],"that":[199,220,238],"DRCV":[200],"has":[201],"great":[202],"application":[203],"prospects":[204],"accurately":[206],"estimating":[207],"imaging.":[212],"applications":[218],"suggest":[219],"provides":[224],"convenient":[226],"approach":[227],"accurate":[230],"estimation":[232],"without":[233],"interventions.":[235],"We":[236],"concluded":[237],"this":[239],"promising":[246],"automatically":[249],"patients":[254],"low-functioning":[256],"kidneys.":[257]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
