{"id":"https://openalex.org/W4382725437","doi":"https://doi.org/10.1007/s11042-023-15984-9","title":"Improving the speed and quality of cancer segmentation using lower resolution pathology images","display_name":"Improving the speed and quality of cancer segmentation using lower resolution pathology images","publication_year":2023,"publication_date":"2023-06-29","ids":{"openalex":"https://openalex.org/W4382725437","doi":"https://doi.org/10.1007/s11042-023-15984-9"},"language":"en","primary_location":{"id":"doi:10.1007/s11042-023-15984-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-023-15984-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11042-023-15984-9.pdf","source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11042-023-15984-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077284304","display_name":"Jieyi Li","orcid":"https://orcid.org/0000-0001-6786-1217"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Jieyi Li","raw_affiliation_strings":["Amsterdam Business School, University of Amsterdam, Plantage Muidergracht 12, Amsterdam, 1018 TV, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0001-6786-1217","affiliations":[{"raw_affiliation_string":"Amsterdam Business School, University of Amsterdam, Plantage Muidergracht 12, Amsterdam, 1018 TV, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081822287","display_name":"Anwar Osseyran","orcid":null},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Anwar Osseyran","raw_affiliation_strings":["Amsterdam Business School, University of Amsterdam, Plantage Muidergracht 12, Amsterdam, 1018 TV, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amsterdam Business School, University of Amsterdam, Plantage Muidergracht 12, Amsterdam, 1018 TV, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019214220","display_name":"Ruben Hekster","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruben Hekster","raw_affiliation_strings":["High Performance Machine Learning group, SURF, Science Park 140, Amsterdam, 1098 XG, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"High Performance Machine Learning group, SURF, Science Park 140, Amsterdam, 1098 XG, The Netherlands","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075331928","display_name":"Stevan Rudinac","orcid":"https://orcid.org/0000-0003-1904-8736"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Stevan Rudinac","raw_affiliation_strings":["Amsterdam Business School, University of Amsterdam, Plantage Muidergracht 12, Amsterdam, 1018 TV, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amsterdam Business School, University of Amsterdam, Plantage Muidergracht 12, Amsterdam, 1018 TV, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000465445","display_name":"Valeriu Codreanu","orcid":"https://orcid.org/0000-0002-8348-7998"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Valeriu Codreanu","raw_affiliation_strings":["High Performance Machine Learning group, SURF, Science Park 140, Amsterdam, 1098 XG, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"High Performance Machine Learning group, SURF, Science Park 140, Amsterdam, 1098 XG, The Netherlands","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082752831","display_name":"Damian Podareanu","orcid":"https://orcid.org/0000-0002-4207-8725"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Damian Podareanu","raw_affiliation_strings":["High Performance Machine Learning group, SURF, Science Park 140, Amsterdam, 1098 XG, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"High Performance Machine Learning group, SURF, Science Park 140, Amsterdam, 1098 XG, The Netherlands","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5077284304"],"corresponding_institution_ids":["https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":0.6401,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72659762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"83","issue":"4","first_page":"11999","last_page":"12015"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9976999759674072,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9904000163078308,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8488132953643799},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7760045528411865},{"id":"https://openalex.org/keywords/digital-pathology","display_name":"Digital pathology","score":0.7221423387527466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6544057130813599},{"id":"https://openalex.org/keywords/zoom","display_name":"Zoom","score":0.564125657081604},{"id":"https://openalex.org/keywords/magnification","display_name":"Magnification","score":0.49743011593818665},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4674443006515503},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4590339660644531},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.44341611862182617},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43189069628715515},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.43185022473335266},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4103168845176697},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3840843141078949},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0916820764541626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8488132953643799},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7760045528411865},{"id":"https://openalex.org/C2777522853","wikidata":"https://www.wikidata.org/wiki/Q5276128","display_name":"Digital pathology","level":2,"score":0.7221423387527466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6544057130813599},{"id":"https://openalex.org/C124913957","wikidata":"https://www.wikidata.org/wiki/Q1232548","display_name":"Zoom","level":3,"score":0.564125657081604},{"id":"https://openalex.org/C4144372","wikidata":"https://www.wikidata.org/wiki/Q675287","display_name":"Magnification","level":2,"score":0.49743011593818665},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4674443006515503},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4590339660644531},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.44341611862182617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43189069628715515},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.43185022473335266},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4103168845176697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3840843141078949},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0916820764541626},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.0},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11042-023-15984-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-023-15984-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11042-023-15984-9.pdf","source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"},{"id":"pmh:oai:dare.uva.nl:openaire/f9a823c1-1428-46ba-9436-163c1e84ebbf","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/improving-the-speed-and-quality-of-cancer-segmentation-using-lower-resolution-pathology-images(f9a823c1-1428-46ba-9436-163c1e84ebbf).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Li, J, Osseyran, A, Hekster, R, Rudinac, S, Codreanu, V & Podareanu, D 2024, 'Improving the speed and quality of cancer segmentation using lower resolution pathology images', Multimedia Tools and Applications, vol. 83, no. 4, pp. 11999-12015. https://doi.org/10.1007/s11042-023-15984-9","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s11042-023-15984-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-023-15984-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11042-023-15984-9.pdf","source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4382725437.pdf"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1977653087","https://openalex.org/W1997864537","https://openalex.org/W2133059825","https://openalex.org/W2155653793","https://openalex.org/W2302302587","https://openalex.org/W2509455759","https://openalex.org/W2751723768","https://openalex.org/W2772723798","https://openalex.org/W2794284562","https://openalex.org/W2912208425","https://openalex.org/W2921577390","https://openalex.org/W2930208220","https://openalex.org/W2964309882","https://openalex.org/W2991430586","https://openalex.org/W3003545729","https://openalex.org/W3016480885","https://openalex.org/W3017966379","https://openalex.org/W3042703854","https://openalex.org/W3080854745","https://openalex.org/W3092560349","https://openalex.org/W3100003598","https://openalex.org/W3113478493","https://openalex.org/W3123982987","https://openalex.org/W3128669428","https://openalex.org/W3165730810","https://openalex.org/W3209855943","https://openalex.org/W4200124967","https://openalex.org/W4210589605","https://openalex.org/W4224282129","https://openalex.org/W4282946997","https://openalex.org/W4291019968","https://openalex.org/W4306181160","https://openalex.org/W4313443727","https://openalex.org/W4319214685","https://openalex.org/W4319866410","https://openalex.org/W6602452458"],"related_works":["https://openalex.org/W4255540734","https://openalex.org/W2502757031","https://openalex.org/W4248609557","https://openalex.org/W2951391129","https://openalex.org/W4206296868","https://openalex.org/W2944724518","https://openalex.org/W2291847203","https://openalex.org/W2150244549","https://openalex.org/W4225258897","https://openalex.org/W4382725437"],"abstract_inverted_index":{"Abstract":[0],"In":[1],"this":[2],"paper,":[3],"we":[4,157],"propose":[5],"a":[6,88,99,151],"pipeline":[7],"to":[8],"investigate":[9],"the":[10,45,72,75,83,104,114,123,132,137,147,160,177],"performance":[11,47,73],"of":[12,66,74,91,116,173],"semantic":[13,79,100],"segmentation":[14,42,80,101],"model":[15,43,102,161],"that":[16,159,191],"employs":[17],"an":[18],"encoder-decoder":[19],"architecture":[20],"with":[21,37,60,153],"atrous":[22],"separable":[23],"convolution":[24],"and":[25,77,93,96,141],"spatial":[26],"pyramid":[27],"pooling,":[28],"trained":[29,135,162],"on":[30,48,82,103,136,163,176],"multi-resolution":[31],"whole":[32],"slide":[33],"breast":[34],"pathological":[35],"images":[36,110],"different":[38],"patch":[39],"sizes.":[40],"Our":[41],"obtains":[44],"best":[46],"zoom":[49],"level":[50],"2":[51],"(10":[52],"$$\\times":[53],"$$":[54],"<mml:math":[55],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">":[56],"<mml:mo>\u00d7</mml:mo>":[57],"</mml:math>":[58],"magnification)":[59],"AUC":[61],"score":[62],"0.974":[63],"in":[64],"terms":[65],"slide-level":[67],"classification.":[68],"This":[69,181],"outperforms":[70],"both":[71],"pathologist":[76,152],"other":[78],"models":[81],"Camelyon16":[84],"dataset.":[85],"By":[86,121],"offering":[87],"larger":[89],"field":[90],"view":[92],"reducing":[94],"noise":[95],"detail,":[97],"training":[98],"properly":[105],"selected":[106],"lower":[107,164],"resolution":[108,139,165,179],"pathology":[109],"can":[111,167],"further":[112],"improve":[113],"precision":[115],"pixel-wise":[117],"cancer":[118,174],"region":[119,175],"segmentation.":[120],"contrast,":[122],"corresponding":[124],"inference":[125,133],"time":[126,134,148,154],"is":[127,143],"14":[128],"times":[129],"shorter":[130,145],"than":[131,146],"highest":[138,178],"patches,":[140],"it":[142],"also":[144],"required":[149],"by":[150],"constraints.":[155],"Moreover,":[156],"prove":[158],"patches":[166],"still":[168],"generate":[169],"refined":[170],"external":[171],"polygons":[172],"image.":[180],"study":[182],"provides":[183],"new":[184],"insights":[185],"into":[186],"efficient":[187],"gigapixel":[188],"histopathology":[189],"analysis":[190],"will":[192],"make":[193],"clinical":[194],"adoption":[195],"more":[196],"likely.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}