{"id":"https://openalex.org/W4402454639","doi":"https://doi.org/10.1145/3674029.3674057","title":"Lung Nodule Detection Using K-Means Segmentation and V-Net","display_name":"Lung Nodule Detection Using K-Means Segmentation and V-Net","publication_year":2024,"publication_date":"2024-05-24","ids":{"openalex":"https://openalex.org/W4402454639","doi":"https://doi.org/10.1145/3674029.3674057"},"language":"en","primary_location":{"id":"doi:10.1145/3674029.3674057","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3674029.3674057","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3674029.3674057?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 9th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3674029.3674057?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108813479","display_name":"Qi Xin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163399","display_name":"Shandong First Medical University","ror":"https://ror.org/05jb9pq57","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163399"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Xin","raw_affiliation_strings":["Shandong First Medical University and Shandong Academy of Medical Sciences, China"],"raw_orcid":"https://orcid.org/0009-0001-2651-0979","affiliations":[{"raw_affiliation_string":"Shandong First Medical University and Shandong Academy of Medical Sciences, China","institution_ids":["https://openalex.org/I4210163399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020967511","display_name":"Peng Lei","orcid":"https://orcid.org/0000-0002-2791-0966"},"institutions":[{"id":"https://openalex.org/I4210163399","display_name":"Shandong First Medical University","ror":"https://ror.org/05jb9pq57","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163399"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Peng","raw_affiliation_strings":["Shandong First Medical University and Shandong Academy of Medical Sciences, China"],"raw_orcid":"https://orcid.org/0000-0002-2791-0966","affiliations":[{"raw_affiliation_string":"Shandong First Medical University and Shandong Academy of Medical Sciences, China","institution_ids":["https://openalex.org/I4210163399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000199858","display_name":"Lanhua Zhang","orcid":"https://orcid.org/0000-0003-3895-1170"},"institutions":[{"id":"https://openalex.org/I4210163399","display_name":"Shandong First Medical University","ror":"https://ror.org/05jb9pq57","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163399"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lanhua Zhang","raw_affiliation_strings":["Shandong First Medical University and Shandong Academy of Medical Sciences, China"],"raw_orcid":"https://orcid.org/0000-0003-3895-1170","affiliations":[{"raw_affiliation_string":"Shandong First Medical University and Shandong Academy of Medical Sciences, China","institution_ids":["https://openalex.org/I4210163399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070468625","display_name":"Xiuyun Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163399","display_name":"Shandong First Medical University","ror":"https://ror.org/05jb9pq57","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163399"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuyun Yang","raw_affiliation_strings":["Shandong First Medical University and Shandong Academy of Medical Sciences, China"],"raw_orcid":"https://orcid.org/0009-0007-0517-472X","affiliations":[{"raw_affiliation_string":"Shandong First Medical University and Shandong Academy of Medical Sciences, China","institution_ids":["https://openalex.org/I4210163399"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5108813479"],"corresponding_institution_ids":["https://openalex.org/I4210163399"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27232409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"170","last_page":"174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9731000065803528,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.933899998664856,"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/nodule","display_name":"Nodule (geology)","score":0.6118515729904175},{"id":"https://openalex.org/keywords/lung","display_name":"Lung","score":0.5549196600914001},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4665650427341461},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4493353068828583},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.41212737560272217},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3429318368434906},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.23283395171165466},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.12965789437294006},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.12168863415718079}],"concepts":[{"id":"https://openalex.org/C2776731575","wikidata":"https://www.wikidata.org/wiki/Q2916245","display_name":"Nodule (geology)","level":2,"score":0.6118515729904175},{"id":"https://openalex.org/C2777714996","wikidata":"https://www.wikidata.org/wiki/Q7886","display_name":"Lung","level":2,"score":0.5549196600914001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4665650427341461},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4493353068828583},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.41212737560272217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3429318368434906},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.23283395171165466},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.12965789437294006},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.12168863415718079},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3674029.3674057","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3674029.3674057","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3674029.3674057?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 9th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3674029.3674057","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3674029.3674057","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3674029.3674057?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 9th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320328999","display_name":"Shandong First Medical University","ror":null},{"id":"https://openalex.org/F4320329000","display_name":"Shandong Academy of Medical Sciences","ror":"https://ror.org/05jb9pq57"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402454639.pdf"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2127218421","https://openalex.org/W2272984102","https://openalex.org/W2322371438","https://openalex.org/W2526468814","https://openalex.org/W2962949934","https://openalex.org/W3003415550","https://openalex.org/W3088134661","https://openalex.org/W3185052070","https://openalex.org/W4245551996","https://openalex.org/W4254511140","https://openalex.org/W4298301991"],"related_works":["https://openalex.org/W1964806738","https://openalex.org/W4243779904","https://openalex.org/W2332066440","https://openalex.org/W4377691549","https://openalex.org/W2056973590","https://openalex.org/W3164196203","https://openalex.org/W2475288000","https://openalex.org/W2965938661","https://openalex.org/W2428333999","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Lung":[0],"cancer":[1,90],"is":[2,42,62],"a":[3],"leading":[4],"cause":[5],"of":[6,22],"mortality":[7],"worldwide,":[8],"highlighting":[9],"the":[10,20,36,68],"need":[11],"for":[12,25,31,64,86],"accurate":[13],"and":[14,29,92],"efficient":[15],"detection":[16,34,66],"methods.":[17],"We":[18],"investigate":[19],"fusion":[21],"K-Means":[23,40],"clustering":[24],"lung":[26,32,46,49,70,81,89],"image":[27],"segmentation":[28],"V-Net":[30,60],"nodule":[33,57,65],"with":[35],"LUNA16":[37],"dataset.":[38],"The":[39,59,72],"algorithm":[41],"used":[43,63],"to":[44],"segment":[45],"images,":[47],"isolating":[48],"regions":[50],"from":[51],"surrounding":[52],"tissues,":[53],"which":[54],"facilitates":[55],"subsequent":[56],"detection.":[58],"architecture":[61],"within":[67],"segmented":[69],"regions.":[71],"proposed":[73],"approach":[74],"shows":[75],"promising":[76],"results":[77],"in":[78],"accurately":[79],"identifying":[80],"nodules,":[82],"demonstrating":[83],"its":[84],"potential":[85],"improving":[87],"early":[88],"diagnosis":[91],"patient":[93],"outcomes.":[94]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
