{"id":"https://openalex.org/W2682493750","doi":"https://doi.org/10.1109/isbi.2017.7950660","title":"Adrenal lesions detection on low-contrast CT images using fully convolutional networks with multi-scale integration","display_name":"Adrenal lesions detection on low-contrast CT images using fully convolutional networks with multi-scale integration","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2682493750","doi":"https://doi.org/10.1109/isbi.2017.7950660","mag":"2682493750"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2017.7950660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2017.7950660","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","raw_type":"proceedings-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/A5015039086","display_name":"Lei Bi","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Lei Bi","raw_affiliation_strings":["School of Information Technologies, University of Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information Technologies, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100614820","display_name":"Jinman Kim","orcid":"https://orcid.org/0000-0001-5960-1060"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jinman Kim","raw_affiliation_strings":["School of Information Technologies, University of Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information Technologies, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091321504","display_name":"Tingwei Su","orcid":"https://orcid.org/0000-0001-6472-3492"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I2801556517","display_name":"Ruijin Hospital","ror":"https://ror.org/01hv94n30","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801556517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingwei Su","raw_affiliation_strings":["Ruijin Hospital, Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Ruijin Hospital, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I2801556517","https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082979981","display_name":"Michael Fulham","orcid":"https://orcid.org/0000-0003-0602-6319"},"institutions":[{"id":"https://openalex.org/I2799732068","display_name":"Royal Prince Alfred Hospital","ror":"https://ror.org/05gpvde20","country_code":"AU","type":"healthcare","lineage":["https://openalex.org/I2799732068"]},{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Michael Fulham","raw_affiliation_strings":["Department of PET and Nuclear Medicine, Royal Prince Alfred Hospital, Australia","Sydney Medical School, University of Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Department of PET and Nuclear Medicine, Royal Prince Alfred Hospital, Australia","institution_ids":["https://openalex.org/I2799732068"]},{"raw_affiliation_string":"Sydney Medical School, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068891693","display_name":"Dagan Feng","orcid":"https://orcid.org/0000-0002-3381-214X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Dagan Feng","raw_affiliation_strings":["Med-X Research Institute, Shanghai Jiao Tong University, China","School of Information Technologies, University of Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Med-X Research Institute, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"School of Information Technologies, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069611208","display_name":"Guang Ning","orcid":"https://orcid.org/0000-0002-5754-7635"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I2801556517","display_name":"Ruijin Hospital","ror":"https://ror.org/01hv94n30","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801556517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Ning","raw_affiliation_strings":["Ruijin Hospital, Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Ruijin Hospital, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I2801556517","https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5015039086"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.09359616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"42","issue":null,"first_page":"895","last_page":"898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9955000281333923,"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"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9955000281333923,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9948999881744385,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9848999977111816,"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/contrast","display_name":"Contrast (vision)","score":0.7415173649787903},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.6422896385192871},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6380319595336914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.580893337726593},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5186902284622192},{"id":"https://openalex.org/keywords/contrast-enhancement","display_name":"Contrast enhancement","score":0.45320892333984375},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4407506287097931},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.41700297594070435},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4013362526893616},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.37737035751342773},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.356992244720459},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2642424702644348},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.21835440397262573},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.12369042634963989}],"concepts":[{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.7415173649787903},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.6422896385192871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380319595336914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.580893337726593},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5186902284622192},{"id":"https://openalex.org/C3018181011","wikidata":"https://www.wikidata.org/wiki/Q6849688","display_name":"Contrast enhancement","level":3,"score":0.45320892333984375},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4407506287097931},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.41700297594070435},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4013362526893616},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.37737035751342773},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.356992244720459},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2642424702644348},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.21835440397262573},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.12369042634963989},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2017.7950660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2017.7950660","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1897243830","https://openalex.org/W1903029394","https://openalex.org/W1923594904","https://openalex.org/W1938929646","https://openalex.org/W1944560526","https://openalex.org/W1992843969","https://openalex.org/W2012369671","https://openalex.org/W2086749537","https://openalex.org/W2110261828","https://openalex.org/W2130926356","https://openalex.org/W2148671379","https://openalex.org/W2166319538","https://openalex.org/W2253429366","https://openalex.org/W2437694626","https://openalex.org/W2558789525","https://openalex.org/W2963173190","https://openalex.org/W6637373629","https://openalex.org/W6639624585","https://openalex.org/W6640351089","https://openalex.org/W6640421982","https://openalex.org/W6640464587","https://openalex.org/W6648737282","https://openalex.org/W6653697024","https://openalex.org/W6671834556"],"related_works":["https://openalex.org/W2163751115","https://openalex.org/W2586608483","https://openalex.org/W4323929292","https://openalex.org/W2988088379","https://openalex.org/W2625093041","https://openalex.org/W2733233723","https://openalex.org/W769135352","https://openalex.org/W4395469579","https://openalex.org/W2415838370","https://openalex.org/W3120218437"],"abstract_inverted_index":{"Adrenal":[0],"lesions":[1,34,60,203,213],"include":[2],"a":[3,136,160,164],"wide":[4],"variety":[5],"of":[6,11,22,27,32,90,97,123,144,204],"benign":[7],"and":[8,15,40,56,80,110,130,139,147,188,191,207,218,226],"malignant":[9],"neoplasms":[10],"the":[12,28,59,68,142,173,186],"adrenal":[13,115,154,202,212],"gland,":[14],"are":[16,61,150],"seen":[17],"in":[18,78,135],"up":[19],"to":[20,64,87,113,171,184,200,222],"5%":[21],"computed":[23],"tomography":[24],"(CT)":[25],"examinations":[26],"abdomen.":[29],"Better":[30],"identification":[31],"these":[33],"is":[35,85],"important":[36],"for":[37,50,153],"effective":[38],"management":[39],"patient":[41],"prognosis.":[42],"Detection":[43],"on":[44,117,176,197,215],"low-contrast":[45,82,118,216],"CT":[46,119,217],"images,":[47],"however,":[48],"even":[49],"experienced":[51],"physicians":[52],"can":[53],"be":[54,65],"difficult":[55],"error-prone,":[57],"because":[58],"often":[62],"problematic":[63],"separated":[66],"from":[67],"normal":[69],"surrounding":[70],"structures.":[71],"Existing":[72],"lesion":[73,116,155,174],"detection":[74,233],"techniques":[75],"have":[76],"problems":[77],"identifying":[79],"differentiating":[81],"tumors,":[83],"which":[84,149],"related":[86],"their":[88],"use":[89,193],"low-level":[91],"features":[92],"rather":[93],"than":[94],"high":[95],"level":[96],"semantics.":[98],"Hence":[99],"we":[100],"propose":[101,159],"an":[102],"automated":[103],"approach":[104,170,221,230],"using":[105],"fully":[106],"convolutional":[107],"networks":[108],"(FCNs)":[109],"multi-scale":[111,161],"integration":[112,162],"detect":[114,201],"scans.":[120],"The":[121,179],"architecture":[122],"FCNs":[124],"includes":[125],"deep,":[126],"coarse,":[127],"semantic":[128],"information":[129,134,195],"shallow,":[131],"fine,":[132],"appearance":[133,189],"hierarchical":[137],"manner":[138],"it":[140],"enables":[141,182],"encoding":[143],"image-wide":[145],"location":[146],"semantics,":[148],"desirable":[151],"characteristics":[152],"detection.":[156],"We":[157,209],"also":[158],"with":[163],"superpixel":[165],"based":[166],"random":[167],"walk":[168],"(MI-SRW)":[169],"refine":[172],"boundaries":[175],"different":[177,198],"scales.":[178],"MI-SRW":[180],"technique":[181],"us":[183],"constrain":[185],"spatial":[187],"consistency":[190],"then":[192],"complementary":[194],"provided":[196],"scales":[199],"various":[205],"sizes":[206],"characteristics.":[208],"used":[210],"38":[211],"detected":[214],"compared":[219],"our":[220,229],"existing":[223],"`state-of-the-art'":[224],"methods":[225],"found":[227],"that":[228],"had":[231],"superior":[232],"performance.":[234]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
