{"id":"https://openalex.org/W2503782659","doi":"https://doi.org/10.1109/snpd.2016.7515975","title":"Features extraction of prostate with graph spectral method for prostate cancer detection","display_name":"Features extraction of prostate with graph spectral method for prostate cancer detection","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2503782659","doi":"https://doi.org/10.1109/snpd.2016.7515975","mag":"2503782659"},"language":"en","primary_location":{"id":"doi:10.1109/snpd.2016.7515975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2016.7515975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","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/A5054796388","display_name":"Weiwei Du","orcid":"https://orcid.org/0000-0002-5133-5615"},"institutions":[{"id":"https://openalex.org/I27429435","display_name":"Kyoto Institute of Technology","ror":"https://ror.org/00965ax52","country_code":"JP","type":"education","lineage":["https://openalex.org/I27429435"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Weiwei Du","raw_affiliation_strings":["Department of Information Science, Kyoto Institute of Technology, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information Science, Kyoto Institute of Technology, Kyoto, Japan","institution_ids":["https://openalex.org/I27429435"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051392113","display_name":"Yipeng Liu","orcid":"https://orcid.org/0000-0001-8658-5764"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi-peng Liu","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103209041","display_name":"Shiyang Wang","orcid":"https://orcid.org/0000-0001-8920-6221"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiyang Wang","raw_affiliation_strings":["Department of Radiology, The University of Chicago, Chicago, Illinois, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, The University of Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089537405","display_name":"Yahui Peng","orcid":"https://orcid.org/0000-0002-2520-1170"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yahui Peng","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005934773","display_name":"Aytekin Oto","orcid":"https://orcid.org/0000-0003-4325-2489"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aytekin Oto","raw_affiliation_strings":["Department of Radiology, The University of Chicago, Chicago, Illinois, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, The University of Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5054796388"],"corresponding_institution_ids":["https://openalex.org/I27429435"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56008861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"192","issue":null,"first_page":"663","last_page":"668"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9940000176429749,"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":0.9940000176429749,"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/T10862","display_name":"AI in cancer detection","score":0.9797999858856201,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9653000235557556,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prostate-cancer","display_name":"Prostate cancer","score":0.7477580904960632},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.6882728338241577},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6246504783630371},{"id":"https://openalex.org/keywords/prostate","display_name":"Prostate","score":0.6220973134040833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5433058142662048},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.531692385673523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4695207476615906},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.45215439796447754},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4340721368789673},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3875597417354584},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31867605447769165},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.28813406825065613},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.21711599826812744},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1088557243347168},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.08152124285697937}],"concepts":[{"id":"https://openalex.org/C2780192828","wikidata":"https://www.wikidata.org/wiki/Q181257","display_name":"Prostate cancer","level":3,"score":0.7477580904960632},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.6882728338241577},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6246504783630371},{"id":"https://openalex.org/C2776235491","wikidata":"https://www.wikidata.org/wiki/Q9625","display_name":"Prostate","level":3,"score":0.6220973134040833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5433058142662048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.531692385673523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4695207476615906},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.45215439796447754},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4340721368789673},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3875597417354584},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31867605447769165},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.28813406825065613},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.21711599826812744},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1088557243347168},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.08152124285697937},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snpd.2016.7515975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2016.7515975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2017830195","https://openalex.org/W2046168168","https://openalex.org/W2107030642","https://openalex.org/W2138136995","https://openalex.org/W2231156824"],"related_works":["https://openalex.org/W299695548","https://openalex.org/W2384122898","https://openalex.org/W151774199","https://openalex.org/W4281885123","https://openalex.org/W2345040638","https://openalex.org/W3171449477","https://openalex.org/W2088520467","https://openalex.org/W2075763133","https://openalex.org/W2376423713","https://openalex.org/W1583600832"],"abstract_inverted_index":{"Prostate":[0],"cancers":[1],"were":[2],"segmented":[3],"directly":[4],"in":[5,8,26,71,83],"T2-weighted":[6,27],"images":[7],"some":[9,30,50,67,118],"studies":[10],"of":[11,74],"computer-aided":[12],"detection":[13],"(CAD).":[14],"These":[15],"methods":[16],"don't":[17],"consider":[18,42],"the":[19,43,72],"differences":[20,44,78,119],"between":[21,45,79,120],"lesion":[22,46,121],"and":[23,47,81,122],"non-lesion":[24,48,123],"region":[25,73],"images,":[28],"so":[29],"lesions":[31],"are":[32,69,87],"not":[33],"easy":[34],"to":[35,41,76,99],"be":[36],"detected.":[37],"In":[38],"this":[39],"paper,":[40],"region,":[49],"features":[51,105],"extraction":[52],"is":[53,63],"proposed":[54],"by":[55,94,111],"using":[56,95,112],"graph":[57,96,113],"spectral":[58,97,114],"method.":[59],"First,":[60],"whole":[61],"prostate":[62,75,101],"extracted.":[64],"And":[65],"then,":[66],"statistics":[68,86],"computed":[70],"find":[77,117],"cancer":[80],"noncancer":[82],"prostate.":[84],"The":[85],"mapped":[88],"into":[89],"m":[90,107],"dimensional":[91,108],"Euclidean":[92,109],"space":[93,110],"method":[98,115],"detect":[100],"cancers.":[102],"Experiments":[103],"show":[104],"with":[106],"can":[116],"region.":[124]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
