{"id":"https://openalex.org/W4404925422","doi":"https://doi.org/10.1145/3696271.3696308","title":"Accurate Delineation of Multiple CT Liver Lesions by Deep Processing of Image Patches","display_name":"Accurate Delineation of Multiple CT Liver Lesions by Deep Processing of Image Patches","publication_year":2024,"publication_date":"2024-08-02","ids":{"openalex":"https://openalex.org/W4404925422","doi":"https://doi.org/10.1145/3696271.3696308"},"language":"en","primary_location":{"id":"doi:10.1145/3696271.3696308","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3696271.3696308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 7th International Conference on Machine Learning and Machine Intelligence (MLMI)","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/A5013686014","display_name":"Arzhang Javadi","orcid":null},"institutions":[{"id":"https://openalex.org/I119025939","display_name":"Shahed University","ror":"https://ror.org/01e8ff003","country_code":"IR","type":"education","lineage":["https://openalex.org/I119025939"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Alireza Javadi","raw_affiliation_strings":["Department of Biomedical Engineering, Engineering Faculty, Shahed University, Tehran, Iran"],"raw_orcid":"https://orcid.org/0000-0002-6180-426X","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Engineering Faculty, Shahed University, Tehran, Iran","institution_ids":["https://openalex.org/I119025939"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083154285","display_name":"Amir Hossein Foruzan","orcid":"https://orcid.org/0000-0003-0177-3227"},"institutions":[{"id":"https://openalex.org/I119025939","display_name":"Shahed University","ror":"https://ror.org/01e8ff003","country_code":"IR","type":"education","lineage":["https://openalex.org/I119025939"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Amir Hossein Foruzan","raw_affiliation_strings":["Department of Biomedical Engineering, Engineering Faculty, Shahed University, Tehran, Iran"],"raw_orcid":"https://orcid.org/0000-0003-0177-3227","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Engineering Faculty, Shahed University, Tehran, Iran","institution_ids":["https://openalex.org/I119025939"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044216245","display_name":"Yen\u2010Wei Chen","orcid":"https://orcid.org/0000-0002-5952-0188"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yen-Wei Chen","raw_affiliation_strings":["Intelligent Image Processing Lab, College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5952-0188","affiliations":[{"raw_affiliation_string":"Intelligent Image Processing Lab, College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan","institution_ids":["https://openalex.org/I135768898"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"235","last_page":"239"},"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":0.9980999827384949,"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":0.9980999827384949,"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":0.995199978351593,"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/T10862","display_name":"AI in cancer detection","score":0.989799976348877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5940267443656921},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5038926005363464},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4900404214859009},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4295910894870758},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36119818687438965},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3317985534667969},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.28039950132369995}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5940267443656921},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5038926005363464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4900404214859009},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4295910894870758},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36119818687438965},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3317985534667969},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.28039950132369995}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3696271.3696308","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3696271.3696308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 7th International Conference on Machine Learning and Machine Intelligence (MLMI)","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":9,"referenced_works":["https://openalex.org/W3010749409","https://openalex.org/W3126512887","https://openalex.org/W3195042084","https://openalex.org/W4281666884","https://openalex.org/W4285731970","https://openalex.org/W4298152023","https://openalex.org/W4313897319","https://openalex.org/W4379745795","https://openalex.org/W4387211701"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"One":[0],"of":[1,5,21,32,37,53,101],"the":[2,30,35,51,58,72,99,111,115],"primary":[3],"causes":[4],"death":[6],"is":[7,47],"liver":[8,10,22,68],"cancer-related":[9],"abnormalities.":[11,23],"Finding":[12],"a":[13,40,48,64,82],"trustworthy":[14],"treatment":[15],"plan":[16],"needs":[17],"an":[18],"early":[19],"diagnosis":[20],"Available":[24],"convolutional":[25],"neural":[26],"networks":[27],"cannot":[28],"identify":[29],"region":[31],"interest":[33],"and":[34,107,122,128],"number":[36],"lesions":[38],"in":[39,42,50],"slice":[41,88],"CT":[43],"images.":[44],"Furthermore,":[45],"there":[46],"challenge":[49],"detection":[52,70],"small":[54,91],"lesions.":[55],"To":[56],"address":[57],"abovementioned":[59],"problems,":[60],"this":[61],"paper":[62],"presents":[63],"novel":[65],"approach":[66],"for":[67,85],"lesion":[69],"using":[71],"You":[73],"Only":[74],"Look":[75],"Ones":[76],"(Yolo)":[77],"8":[78],"network.":[79],"It":[80],"proposes":[81],"preprocessing":[83],"method":[84,117],"dividing":[86],"each":[87],"into":[89],"overlapping":[90],"patches.":[92],"We":[93],"used":[94],"four":[95],"metrics":[96],"to":[97],"validate":[98],"performance":[100],"our":[102],"method:":[103],"precision,":[104,125],"recall,":[105,126],"F1-score,":[106,127],"hit-and-miss":[108,129],"ratio.":[109,130],"On":[110],"3DirCADb":[112],"public":[113],"dataset,":[114],"proposed":[116],"achieved":[118],"97%,":[119],"78%,":[120],"87%,":[121],"82%":[123],"concerning":[124]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}