{"id":"https://openalex.org/W3091528702","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206868","title":"Axis projection for Kidney-Region-Of-Interest detection in computed tomography","display_name":"Axis projection for Kidney-Region-Of-Interest detection in computed tomography","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3091528702","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206868","mag":"3091528702"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5064563538","display_name":"Tomasz Le\u015b","orcid":"https://orcid.org/0000-0001-6131-9080"},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Tomasz Les","raw_affiliation_strings":["Warsaw University of Technology, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Warsaw University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I108403487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058080492","display_name":"Tomasz Markiewcz","orcid":null},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Tomasz Markiewcz","raw_affiliation_strings":["Military Institute of Medicine, Warsaw University of Technology, Warsaw, Ponad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Military Institute of Medicine, Warsaw University of Technology, Warsaw, Ponad","institution_ids":["https://openalex.org/I108403487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084562393","display_name":"Miros\u0142aw Dziekiewicz","orcid":"https://orcid.org/0000-0003-2504-6462"},"institutions":[{"id":"https://openalex.org/I4210121233","display_name":"Wojskowy Instytut Medycyny Lotniczej","ror":"https://ror.org/01xtcza13","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210121233"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Miroslaw Dziekiewicz","raw_affiliation_strings":["Military Institute of Medicine, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Military Institute of Medicine, Warsaw, Poland","institution_ids":["https://openalex.org/I4210121233"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076585902","display_name":"Ma\u0142gorzata Lorent","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121233","display_name":"Wojskowy Instytut Medycyny Lotniczej","ror":"https://ror.org/01xtcza13","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210121233"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Malgorzata Lorent","raw_affiliation_strings":["Military Institute of Medicine, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Military Institute of Medicine, Warsaw, Poland","institution_ids":["https://openalex.org/I4210121233"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1709,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47800904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3361","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9850999712944031,"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":0.9850999712944031,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9728000164031982,"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":0.9456999897956848,"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/projection","display_name":"Projection (relational algebra)","score":0.7227044105529785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6612769961357117},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6313146352767944},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6301316022872925},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6127483248710632},{"id":"https://openalex.org/keywords/envelope","display_name":"Envelope (radar)","score":0.604993462562561},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5471302270889282},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5386616587638855},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.5360517501831055},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5275779962539673},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5054154396057129},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49942541122436523},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.46120232343673706},{"id":"https://openalex.org/keywords/maximum-intensity-projection","display_name":"Maximum intensity projection","score":0.4584789276123047},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4484923183917999},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34017452597618103},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.272259920835495},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2228637933731079},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.08514553308486938},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08122208714485168},{"id":"https://openalex.org/keywords/angiography","display_name":"Angiography","score":0.07873877882957458},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06906864047050476}],"concepts":[{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.7227044105529785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6612769961357117},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6313146352767944},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6301316022872925},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6127483248710632},{"id":"https://openalex.org/C65155139","wikidata":"https://www.wikidata.org/wiki/Q5380912","display_name":"Envelope (radar)","level":3,"score":0.604993462562561},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5471302270889282},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5386616587638855},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.5360517501831055},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5275779962539673},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5054154396057129},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49942541122436523},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.46120232343673706},{"id":"https://openalex.org/C110021049","wikidata":"https://www.wikidata.org/wiki/Q1539231","display_name":"Maximum intensity projection","level":3,"score":0.4584789276123047},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4484923183917999},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34017452597618103},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.272259920835495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2228637933731079},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.08514553308486938},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08122208714485168},{"id":"https://openalex.org/C2780643987","wikidata":"https://www.wikidata.org/wiki/Q468414","display_name":"Angiography","level":2,"score":0.07873877882957458},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06906864047050476},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W22040386","https://openalex.org/W1538131130","https://openalex.org/W2112796928","https://openalex.org/W2124611117","https://openalex.org/W2171417304","https://openalex.org/W2387001731","https://openalex.org/W2588652678","https://openalex.org/W2597711478","https://openalex.org/W2885990802","https://openalex.org/W2933796343","https://openalex.org/W4233852058","https://openalex.org/W6632100814","https://openalex.org/W6742383601","https://openalex.org/W6753759471","https://openalex.org/W6761292208"],"related_works":["https://openalex.org/W2002088038","https://openalex.org/W2090363770","https://openalex.org/W2073227694","https://openalex.org/W1974173024","https://openalex.org/W2983473129","https://openalex.org/W2415097577","https://openalex.org/W2126798690","https://openalex.org/W2317976588","https://openalex.org/W2021107780","https://openalex.org/W2049309852"],"abstract_inverted_index":{"The":[0,12,42,91,110],"article":[1],"presents":[2],"an":[3],"innovative":[4],"method":[5,74,93],"of":[6,19,35,48,53,79,86,99,119,128,137],"scanning":[7],"slices":[8],"in":[9,117],"computed":[10],"tomography.":[11],"presented":[13,43,92,111,126],"technique":[14,44,98,112],"allows":[15],"for":[16,38,62,65,88],"automatically":[17],"generation":[18],"three-dimensional":[20],"projection,":[21],"determined":[22],"by":[23,133,144],"X-Y-Z":[24,129],"surfaces.":[25],"Projections":[26],"allow":[27],"to":[28,140],"calculate":[29],"Kidney-Region-Of-Interest":[30],"-":[31],"a":[32,58,134,145],"minimal":[33],"envelope":[34],"kidney":[36,67,80],"contours":[37],"all":[39],"CT":[40,71],"scans.":[41,72],"increases":[45],"the":[46,77,84,97,120,141],"accuracy":[47],"automatic":[49],"identification":[50,87],"and":[51,55,107],"segmentation":[52],"kidneys":[54],"can":[56],"be":[57],"good":[59],"starting":[60],"point":[61],"other":[63],"techniques":[64],"identifying":[66],"areas":[68],"on":[69,96],"individual":[70],"This":[73],"significantly":[75],"limits":[76],"area":[78,104],"searching,":[81],"thereby":[82],"accelerates":[83],"operation":[85],"any":[89],"algorithm.":[90],"is":[94,131],"based":[95],"pixel":[100],"intensity":[101],"values":[102],"averaging,":[103],"region-growing":[105],"algorithms":[106],"morphological":[108],"transformations.":[109],"has":[113],"also":[114],"been":[115],"tested":[116],"implementation":[118],"U-Net":[121],"neural":[122],"network":[123],"system.":[124],"Our":[125],"solution":[127],"projection":[130],"characterized":[132],"high":[135],"efficiency":[136],"visualization,":[138],"comparable":[139],"results":[142],"obtained":[143],"human":[146],"expert.":[147]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
