{"id":"https://openalex.org/W3115420299","doi":"https://doi.org/10.1109/tbme.2020.3046252","title":"Small Blob Detector Using Bi-Threshold Constrained Adaptive Scales","display_name":"Small Blob Detector Using Bi-Threshold Constrained Adaptive Scales","publication_year":2020,"publication_date":"2020-12-21","ids":{"openalex":"https://openalex.org/W3115420299","doi":"https://doi.org/10.1109/tbme.2020.3046252","mag":"3115420299","pmid":"https://pubmed.ncbi.nlm.nih.gov/33347401"},"language":"en","primary_location":{"id":"doi:10.1109/tbme.2020.3046252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2020.3046252","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biomedical Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8461780","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044992422","display_name":"Yanzhe Xu","orcid":"https://orcid.org/0000-0002-6221-8676"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanzhe Xu","raw_affiliation_strings":["Informatics and Decision Systems Engineering and ASU-Mayo Center for Innovative Imaging, School of Computing, Arizona State University, USA"],"raw_orcid":"https://orcid.org/0000-0002-6221-8676","affiliations":[{"raw_affiliation_string":"Informatics and Decision Systems Engineering and ASU-Mayo Center for Innovative Imaging, School of Computing, Arizona State University, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069823101","display_name":"Teresa Wu","orcid":"https://orcid.org/0000-0002-0529-7048"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Teresa Wu","raw_affiliation_strings":["Informatics and Decision Systems Engineering, and ASU-Mayo Center for Innovative Imaging, School of Computing, Arizona State University, Tempe, AZ, USA"],"raw_orcid":"https://orcid.org/0000-0002-0529-7048","affiliations":[{"raw_affiliation_string":"Informatics and Decision Systems Engineering, and ASU-Mayo Center for Innovative Imaging, School of Computing, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032458123","display_name":"Jennifer R. Charlton","orcid":"https://orcid.org/0000-0002-2225-535X"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer R. Charlton","raw_affiliation_strings":["Department of Pediatrics, Division Nephrology, University of Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Pediatrics, Division Nephrology, University of Virginia, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101652486","display_name":"Fei Gao","orcid":"https://orcid.org/0000-0001-5675-1899"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Gao","raw_affiliation_strings":["Informatics and Decision Systems Engineering and ASU-Mayo Center for Innovative Imaging, School of Computing, Arizona State University, USA"],"raw_orcid":"https://orcid.org/0000-0001-5675-1899","affiliations":[{"raw_affiliation_string":"Informatics and Decision Systems Engineering and ASU-Mayo Center for Innovative Imaging, School of Computing, Arizona State University, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002902508","display_name":"Kevin M. Bennett","orcid":"https://orcid.org/0000-0003-1706-4660"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kevin M. Bennett","raw_affiliation_strings":["Department of Radiology, Washington University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Washington University, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4341,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.86304616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"68","issue":"9","first_page":"2654","last_page":"2665"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10862","display_name":"AI in cancer detection","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9987000226974487,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9973999857902527,"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/blob-detection","display_name":"Blob detection","score":0.762715220451355},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7472326755523682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7410572171211243},{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.685361385345459},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.665176272392273},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.654980480670929},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6015441417694092},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5680437684059143},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5566137433052063},{"id":"https://openalex.org/keywords/scale-space","display_name":"Scale space","score":0.5148438811302185},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49741628766059875},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49665170907974243},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47029897570610046},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31873029470443726},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2695191502571106},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.25411635637283325},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.1580042541027069},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1370934247970581}],"concepts":[{"id":"https://openalex.org/C29168087","wikidata":"https://www.wikidata.org/wiki/Q1026711","display_name":"Blob detection","level":5,"score":0.762715220451355},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7472326755523682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7410572171211243},{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.685361385345459},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.665176272392273},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.654980480670929},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6015441417694092},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5680437684059143},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5566137433052063},{"id":"https://openalex.org/C99102927","wikidata":"https://www.wikidata.org/wiki/Q3058184","display_name":"Scale space","level":4,"score":0.5148438811302185},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49741628766059875},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49665170907974243},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47029897570610046},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31873029470443726},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2695191502571106},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25411635637283325},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.1580042541027069},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1370934247970581},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007668","descriptor_name":"Kidney","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007668","descriptor_name":"Kidney","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007668","descriptor_name":"Kidney","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007668","descriptor_name":"Kidney","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015415","descriptor_name":"Biomarkers","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015415","descriptor_name":"Biomarkers","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015415","descriptor_name":"Biomarkers","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015415","descriptor_name":"Biomarkers","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tbme.2020.3046252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2020.3046252","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biomedical Engineering","raw_type":"journal-article"},{"id":"pmid:33347401","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33347401","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on bio-medical engineering","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8461780","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8461780","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Biomed Eng","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:8461780","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8461780","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Biomed Eng","raw_type":"Text"},"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1341221458","display_name":null,"funder_award_id":"R01DK111861","funder_id":"https://openalex.org/F4320334876","funder_display_name":"Korea National Institute of Health"},{"id":"https://openalex.org/G4110880326","display_name":null,"funder_award_id":"R01 DK111861","funder_id":"https://openalex.org/F4320337357","funder_display_name":"National Institute of Diabetes and Digestive and Kidney Diseases"},{"id":"https://openalex.org/G5926434626","display_name":null,"funder_award_id":"S10 RR019911","funder_id":"https://openalex.org/F4320337375","funder_display_name":"National Center for Research Resources"},{"id":"https://openalex.org/G6472200432","display_name":null,"funder_award_id":"R01 DK110622","funder_id":"https://openalex.org/F4320337357","funder_display_name":"National Institute of Diabetes and Digestive and Kidney Diseases"},{"id":"https://openalex.org/G6992611853","display_name":null,"funder_award_id":"R01DK110622","funder_id":"https://openalex.org/F4320334876","funder_display_name":"Korea National Institute of Health"}],"funders":[{"id":"https://openalex.org/F4320334236","display_name":"School of Medicine, University of Virginia","ror":null},{"id":"https://openalex.org/F4320334876","display_name":"Korea National Institute of Health","ror":"https://ror.org/00qdsfq65"},{"id":"https://openalex.org/F4320337357","display_name":"National Institute of Diabetes and Digestive and Kidney Diseases","ror":"https://ror.org/00adh9b73"},{"id":"https://openalex.org/F4320337375","display_name":"National Center for Research Resources","ror":"https://ror.org/04pw6fb54"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W22040386","https://openalex.org/W1998865404","https://openalex.org/W2012231760","https://openalex.org/W2038472491","https://openalex.org/W2039112550","https://openalex.org/W2044221450","https://openalex.org/W2069463854","https://openalex.org/W2096546754","https://openalex.org/W2107030642","https://openalex.org/W2109200236","https://openalex.org/W2130371234","https://openalex.org/W2133059825","https://openalex.org/W2142332605","https://openalex.org/W2196188554","https://openalex.org/W2207662563","https://openalex.org/W2261275921","https://openalex.org/W2280351290","https://openalex.org/W2395611524","https://openalex.org/W2404945401","https://openalex.org/W2438635651","https://openalex.org/W2504150216","https://openalex.org/W2524399695","https://openalex.org/W2581082771","https://openalex.org/W2596410941","https://openalex.org/W2620591646","https://openalex.org/W2761625450","https://openalex.org/W2767038576","https://openalex.org/W2791942584","https://openalex.org/W2805773775","https://openalex.org/W2807612972","https://openalex.org/W2884833628","https://openalex.org/W2895362160","https://openalex.org/W2900936384","https://openalex.org/W2914010220","https://openalex.org/W2914209001","https://openalex.org/W2918032088","https://openalex.org/W2918405906","https://openalex.org/W2941093521","https://openalex.org/W2945801048","https://openalex.org/W2958500321","https://openalex.org/W2962804068","https://openalex.org/W2962963674","https://openalex.org/W2963228224","https://openalex.org/W2963618258","https://openalex.org/W2972252504","https://openalex.org/W2974160260","https://openalex.org/W2999155059","https://openalex.org/W3033107563","https://openalex.org/W3083896085","https://openalex.org/W3103895001","https://openalex.org/W6676001793","https://openalex.org/W6732209190","https://openalex.org/W6735039561"],"related_works":["https://openalex.org/W3132215033","https://openalex.org/W1968965685","https://openalex.org/W2012231760","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2356903262","https://openalex.org/W2327601824","https://openalex.org/W4237142086"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,35,46],"medical":[3],"imaging":[4],"technology":[5],"bring":[6],"great":[7],"promises":[8],"for":[9],"medicine":[10],"practices.":[11],"Imaging":[12],"biomarkers":[13],"are":[14,30,116,187],"discovered":[15],"to":[16,76,91,125],"inform":[17],"disease":[18],"diagnosis,":[19],"prognosis,":[20],"and":[21,25,60,84,101,146,179,205,212],"treatment":[22],"assessment.":[23],"Detecting":[24],"segmenting":[26],"objects":[27,45,50],"from":[28,108],"images":[29],"often":[31],"the":[32,63,78,81,85,105,114,143,147,151,157,160,220],"first":[33],"steps":[34],"quantitative":[36],"measurement":[37],"of":[38,43,87,113,150,159,170,176,184],"these":[39],"biomarkers.":[40],"The":[41],"challenges":[42],"detecting":[44],"images,":[47],"particularly":[48],"small":[49,96],"known":[51],"as":[52],"blobs,":[53,171],"include":[54],"low":[55],"image":[56,58],"resolution,":[57],"noise":[59],"overlap":[61],"among":[62],"blobs.":[64],"This":[65],"research":[66],"proposes":[67],"a":[68,93,126,163,172,180],"Bi-Threshold":[69],"Constrained":[70],"Adaptive":[71],"Scale":[72],"(BTCAS)":[73],"blob":[74,97,119,122],"detector":[75],"uncover":[77],"relationship":[79],"between":[80,118],"U-Net":[82,152,197,201],"threshold":[83],"Difference":[86],"Gaussian":[88],"(DoG)":[89],"scale":[90],"derive":[92],"multi-threshold,":[94],"multi-scale":[95],"detector.":[98],"With":[99],"lower":[100],"upper":[102],"bounds":[103],"on":[104],"probability":[106],"thresholds":[107],"U-Net,":[109],"two":[110],"binarized":[111],"maps":[112],"distance":[115],"rendered":[117,141],"centers.":[120],"Each":[121],"is":[123,140,153,190],"transformed":[124],"DoG":[127],"space":[128],"with":[129,198,202],"an":[130],"adaptively":[131],"identified":[132],"local":[133],"optimum":[134],"scale.":[135],"A":[136],"Hessian":[137],"convexity":[138],"map":[139],"using":[142,207],"adaptive":[144],"scale,":[145],"under-segmentation":[148],"typical":[149],"resolved.":[154],"To":[155],"validate":[156],"performance":[158],"proposed":[161],"BTCAS,":[162],"3D":[164,173,181],"simulated":[165],"dataset":[166,175,183],"(n":[167],"=":[168],"20)":[169],"MRI":[174,182],"human":[177],"kidneys":[178],"mouse":[185],"kidneys,":[186],"studied.":[188],"BTCAS":[189,217],"compared":[191,221],"against":[192],"four":[193],"state-of-the-art":[194],"methods:":[195],"HDoG,":[196],"standard":[199],"thresholding,":[200,204],"optimal":[203],"UH-DoG":[206],"precision,":[208],"recall,":[209],"F-score,":[210],"Dice":[211],"IoU.":[213],"We":[214],"conclude":[215],"that":[216],"statistically":[218],"outperforms":[219],"detectors.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
