{"id":"https://openalex.org/W3010771748","doi":"https://doi.org/10.1117/12.2550014","title":"A deep learning based integration of multiple texture patterns from intensity, gradient and curvature GLCMs in differentiating the malignant from benign polyps","display_name":"A deep learning based integration of multiple texture patterns from intensity, gradient and curvature GLCMs in differentiating the malignant from benign polyps","publication_year":2020,"publication_date":"2020-03-16","ids":{"openalex":"https://openalex.org/W3010771748","doi":"https://doi.org/10.1117/12.2550014","mag":"3010771748"},"language":"en","primary_location":{"id":"doi:10.1117/12.2550014","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550014","pdf_url":null,"source":{"id":"https://openalex.org/S4306519512","display_name":"Medical Imaging 2020: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Computer-Aided Diagnosis","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/A5100452871","display_name":"Shu Zhang","orcid":"https://orcid.org/0000-0003-3658-3159"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shu Zhang","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101674874","display_name":"Weiguo Cao","orcid":"https://orcid.org/0000-0002-2321-3207"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weiguo Cao","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005714545","display_name":"Marc J. Pomeroy","orcid":"https://orcid.org/0000-0002-3982-1776"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marc Pomeroy","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028884087","display_name":"Yongfeng Gao","orcid":"https://orcid.org/0000-0001-6169-3478"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongfeng Gao","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101972788","display_name":"Jiaxing Tan","orcid":"https://orcid.org/0000-0001-9908-3691"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaxing Tan","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110322946","display_name":"Zhengrong Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengrong Liang","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100452871"],"corresponding_institution_ids":["https://openalex.org/I59553526"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02718644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"118","last_page":"118"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T10862","display_name":"AI in cancer detection","score":0.9991999864578247,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9758999943733215,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8044215440750122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6782172322273254},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.6551895141601562},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6290378570556641},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6274718046188354},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.5842623710632324},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5421217083930969},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.4757504165172577},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.44462907314300537},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.423678994178772},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.419563889503479},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35238850116729736},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26977890729904175},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22806411981582642},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2083415389060974},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16874751448631287}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8044215440750122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6782172322273254},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.6551895141601562},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6290378570556641},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6274718046188354},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.5842623710632324},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5421217083930969},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.4757504165172577},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.44462907314300537},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.423678994178772},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.419563889503479},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35238850116729736},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26977890729904175},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22806411981582642},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2083415389060974},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16874751448631287},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2550014","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550014","pdf_url":null,"source":{"id":"https://openalex.org/S4306519512","display_name":"Medical Imaging 2020: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Computer-Aided Diagnosis","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":0,"referenced_works":[],"related_works":["https://openalex.org/W4385649027","https://openalex.org/W4400094315","https://openalex.org/W2970784617","https://openalex.org/W141820298","https://openalex.org/W2044270176","https://openalex.org/W2374828682","https://openalex.org/W2153116791","https://openalex.org/W2388733570","https://openalex.org/W4230530180","https://openalex.org/W1980033651"],"abstract_inverted_index":{"Deep":[0],"learning":[1,25],"such":[2,89],"as":[3,78,90],"Convolutional":[4],"Neural":[5],"Network":[6],"(CNN)":[7],"has":[8,57,175,189],"demonstrated":[9],"its":[10],"superior":[11],"in":[12,19,32,242],"the":[13,20,62,79,82,106,122,151,160,165],"field":[14],"of":[15,38,50,81,162,167,187,197],"image":[16],"analysis.":[17],"However,":[18,97],"medical":[21],"imaging":[22],"field,":[23],"deep":[24],"faces":[26],"more":[27],"challenges":[28],"for":[29,85,149,192],"tumor":[30],"classification":[31,123,185,226,243],"computer-aided":[33],"diagnosis":[34],"due":[35],"to":[36,60,104,119,139,239],"uncertainties":[37],"lesions":[39],"including":[40],"their":[41,65],"size,":[42,92],"scaling":[43,95],"factor,":[44],"rotation,":[45],"shapes,":[46],"etc.":[47],"Thus,":[48,110],"instead":[49],"feeding":[51],"raw":[52],"images,":[53],"texture-based":[54,136],"CNN":[55,137],"model":[56,116,138],"been":[58,176,190],"designed":[59],"classify":[61],"objects":[63],"with":[64,205,223],"good":[66,87],"attributes.":[67],"For":[68],"example,":[69],"gray":[70],"level":[71],"co-occurrence":[72],"matrix":[73],"(GLCM)":[74],"can":[75],"be":[76,219],"chosen":[77],"descriptor":[80],"texture":[83,102,108,127,146,181,213],"pattern":[84],"many":[86,100],"properties":[88],"uniform":[91],"shape":[93],"invariance,":[94],"invariance.":[96],"there":[98],"are":[99],"different":[101,107,126,180,216],"metrics":[103,217],"measure":[105],"patterns.":[109,128],"an":[111],"effective":[112],"and":[113,144,221,237],"efficient":[114],"integration":[115,234],"is":[117,235],"essential":[118],"further":[120],"improve":[121],"performance":[124,186],"from":[125,153,215],"In":[129],"this":[130],"paper,":[131],"we":[132],"proposed":[133],"a":[134,193,206,224],"multi-channel":[135],"effectively":[140],"integrate":[141],"intensity,":[142],"gradient":[143],"curvature":[145],"patterns":[147,182],"together":[148],"differentiating":[150],"malignant":[152],"benign":[154],"polyps.":[155],"Performance":[156],"was":[157],"evaluated":[158],"by":[159,178],"merit":[161],"area":[163],"under":[164],"curve":[166],"receiver":[168],"operating":[169],"characteristics":[170],"(AUC).":[171],"Around":[172],"0.3~4.8%":[173],"improvement":[174,203,241],"observed":[177],"combining":[179],"together.":[183],"Finally,":[184],"AUC=86.7%":[188],"achieved":[191],"polyp":[194],"mass":[195],"dataset":[196],"87":[198],"samples,":[199],"which":[200],"obtains":[201],"1.8%":[202],"compared":[204],"state-of-the-art":[207],"method.":[208],"The":[209],"results":[210],"indicate":[211],"that":[212,232],"information":[214],"could":[218],"fused":[220],"classified":[222],"better":[225],"performance.":[227],"It":[228],"also":[229],"sheds":[230],"lights":[231],"data":[233],"important":[236],"indispensable":[238],"pursuit":[240],"task.":[244]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
