{"id":"https://openalex.org/W2560879631","doi":"https://doi.org/10.1109/iccabs.2016.7802768","title":"Curvelet-based texture classification of critical Gleason patterns of prostate histological images","display_name":"Curvelet-based texture classification of critical Gleason patterns of prostate histological images","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2560879631","doi":"https://doi.org/10.1109/iccabs.2016.7802768","mag":"2560879631"},"language":"en","primary_location":{"id":"doi:10.1109/iccabs.2016.7802768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccabs.2016.7802768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)","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/A5112202927","display_name":"Wen-Chyi Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wen-Chyi Lin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011896478","display_name":"Ching-Chung Li","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ching-Chung Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062227791","display_name":"Jonathan I. Epstein","orcid":"https://orcid.org/0000-0003-1839-6472"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan I. Epstein","raw_affiliation_strings":["Departments of Urology and Oncology, The Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Departments of Urology and Oncology, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110332793","display_name":"Robert W. Veltri","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert W. Veltri","raw_affiliation_strings":["Departments of Urology and Oncology, The Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Departments of Urology and Oncology, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112202927"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":0.7506,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76981587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10124","display_name":"Prostate Cancer Diagnosis and Treatment","score":0.9805999994277954,"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/T10124","display_name":"Prostate Cancer Diagnosis and Treatment","score":0.9805999994277954,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9667999744415283,"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":0.9440000057220459,"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/curvelet","display_name":"Curvelet","score":0.8414396047592163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7389980554580688},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6575220823287964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6313550472259521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6085442900657654},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5575138330459595},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5325661301612854},{"id":"https://openalex.org/keywords/prostate-cancer","display_name":"Prostate cancer","score":0.439997136592865},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.42665889859199524},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2649229168891907},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1997884213924408},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.12234058976173401},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.11413517594337463},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.10381734371185303}],"concepts":[{"id":"https://openalex.org/C131720326","wikidata":"https://www.wikidata.org/wiki/Q5196075","display_name":"Curvelet","level":4,"score":0.8414396047592163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7389980554580688},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6575220823287964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6313550472259521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6085442900657654},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5575138330459595},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5325661301612854},{"id":"https://openalex.org/C2780192828","wikidata":"https://www.wikidata.org/wiki/Q181257","display_name":"Prostate cancer","level":3,"score":0.439997136592865},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.42665889859199524},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2649229168891907},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1997884213924408},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.12234058976173401},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.11413517594337463},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.10381734371185303},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccabs.2016.7802768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccabs.2016.7802768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W88493464","https://openalex.org/W1516748092","https://openalex.org/W1566046477","https://openalex.org/W1917894041","https://openalex.org/W1985357898","https://openalex.org/W1990132523","https://openalex.org/W1998118468","https://openalex.org/W2005942158","https://openalex.org/W2006115709","https://openalex.org/W2009626029","https://openalex.org/W2010399610","https://openalex.org/W2016098311","https://openalex.org/W2043473776","https://openalex.org/W2048236369","https://openalex.org/W2066512559","https://openalex.org/W2102480024","https://openalex.org/W2115528090","https://openalex.org/W2117395293","https://openalex.org/W2129020851","https://openalex.org/W2129894207","https://openalex.org/W2134993189","https://openalex.org/W2141967861","https://openalex.org/W2147497470","https://openalex.org/W2163352848","https://openalex.org/W2171621204","https://openalex.org/W2180701913","https://openalex.org/W2214596509","https://openalex.org/W2252728384","https://openalex.org/W2294284738","https://openalex.org/W2311701863","https://openalex.org/W2548197316","https://openalex.org/W4293768955","https://openalex.org/W6688351164"],"related_works":["https://openalex.org/W2020709293","https://openalex.org/W3142541301","https://openalex.org/W1585855827","https://openalex.org/W2378906974","https://openalex.org/W4242398081","https://openalex.org/W2146220314","https://openalex.org/W2170080599","https://openalex.org/W2353022594","https://openalex.org/W2049855602","https://openalex.org/W1487808658"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"our":[3],"new":[4],"result":[5,137],"of":[6,12,30,42,54,59,73,103,108,143],"a":[7,83],"study":[8],"on":[9],"machine-aided":[10],"classification":[11],"four":[13,109],"critical":[14],"Gleason":[15,34,38,111],"patterns":[16,32],"with":[17,82,153],"curvelet-based":[18],"texture":[19],"descriptors":[20],"extracted":[21],"from":[22],"prostatic":[23],"histological":[24],"section":[25],"images.":[26],"The":[27,135],"reliable":[28],"recognition":[29],"these":[31],"between":[33],"score":[35,39],"6":[36],"and":[37,51,123,133],"8":[40],"is":[41],"crucial":[43],"importance":[44],"that":[45],"will":[46],"affect":[47],"the":[48],"appropriate":[49],"treatment":[50],"patient's":[52],"quality":[53],"life.":[55],"Higher-order":[56],"statistical":[57],"moments":[58],"fine":[60],"scale":[61],"curvelet":[62],"coefficients":[63],"are":[64],"selected":[65],"as":[66],"discriminative":[67],"features.":[68],"A":[69,101],"two-level":[70],"classifier":[71],"consisting":[72],"two":[74],"Gaussian":[75],"kernel":[76],"support":[77],"vector":[78],"machines,":[79],"each":[80],"incorporated":[81],"pertinent":[84],"voting":[85],"mechanism":[86],"by":[87],"multiple":[88],"windowed":[89],"patches":[90],"in":[91,130],"an":[92,140,148],"image":[93],"for":[94,145],"final":[95],"decision":[96],"making,":[97],"has":[98,127,138],"been":[99,128],"developed.":[100],"set":[102],"Tissue":[104],"MicroArray":[105],"(TMA)":[106],"images":[107],"prominent":[110],"scores":[112],"(GS)":[113],"3":[114,117,122],"+":[115,118,121,125],"3,":[116],"4,":[119],"4":[120,124,126,146],"studied":[129],"machine":[131],"learning":[132],"testing.":[134],"testing":[136],"achieved":[139],"average":[141],"accuracy":[142],"93.75%":[144],"classes,":[147],"outstanding":[149],"performance":[150],"when":[151],"compared":[152],"other":[154],"published":[155],"works.":[156]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}