{"id":"https://openalex.org/W2903557259","doi":"https://doi.org/10.1117/12.2512451","title":"XNet: a convolutional neural network (CNN) implementation for medical x-ray image segmentation suitable for small datasets","display_name":"XNet: a convolutional neural network (CNN) implementation for medical x-ray image segmentation suitable for small datasets","publication_year":2019,"publication_date":"2019-03-15","ids":{"openalex":"https://openalex.org/W2903557259","doi":"https://doi.org/10.1117/12.2512451","mag":"2903557259"},"language":"en","primary_location":{"id":"doi:10.1117/12.2512451","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1812.00548","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Joseph Bullock","orcid":null},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Joseph Bullock","raw_affiliation_strings":["Durham Univ. (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham Univ. (United Kingdom)","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Carolina Cuesta-Lazaro","orcid":null},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Carolina Cuesta-Lazaro","raw_affiliation_strings":["Durham Univ. (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham Univ. (United Kingdom)","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"last","author":{"id":null,"display_name":"Arnau Quera-Bofarull","orcid":null},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Arnau Quera-Bofarull","raw_affiliation_strings":["Durham Univ. (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham Univ. (United Kingdom)","institution_ids":["https://openalex.org/I190082696"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.7328,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.97757328,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"69","last_page":"69"},"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":0.9988999962806702,"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":0.9988999962806702,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9987999796867371,"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":0.9979000091552734,"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/image-segmentation","display_name":"Image segmentation","score":0.6337000131607056},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6288999915122986},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5565000176429749},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5206000208854675},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.517799973487854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5062999725341797},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4828999936580658},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4708999991416931}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480000257492065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6998000144958496},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6337000131607056},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6288999915122986},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5565000176429749},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5206000208854675},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.517799973487854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5062999725341797},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4828999936580658},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4708999991416931},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.46650001406669617},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.3880999982357025},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37950000166893005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3257000148296356},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.2969000041484833},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.288100004196167},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C104317675","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Digital image processing","level":4,"score":0.2635999917984009},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2563999891281128},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2512451","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1812.00548","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1812.00548","pdf_url":"https://arxiv.org/pdf/1812.00548","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1812.00548","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1812.00548","pdf_url":"https://arxiv.org/pdf/1812.00548","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1751159142","display_name":null,"funder_award_id":"1941820","funder_id":"https://openalex.org/F4320334632","funder_display_name":"Science and Technology Facilities Council"},{"id":"https://openalex.org/G7609846582","display_name":null,"funder_award_id":"1941883","funder_id":"https://openalex.org/F4320334632","funder_display_name":"Science and Technology Facilities Council"},{"id":"https://openalex.org/G764792286","display_name":null,"funder_award_id":"ST/H008519/1","funder_id":"https://openalex.org/F4320334632","funder_display_name":"Science and Technology Facilities Council"},{"id":"https://openalex.org/G8986044568","display_name":null,"funder_award_id":"ST/K00042X/1","funder_id":"https://openalex.org/F4320334632","funder_display_name":"Science and Technology Facilities Council"}],"funders":[{"id":"https://openalex.org/F4320334632","display_name":"Science and Technology Facilities Council","ror":"https://ror.org/057g20z61"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W156779288","https://openalex.org/W1745334888","https://openalex.org/W1812394418","https://openalex.org/W1898703532","https://openalex.org/W1903029394","https://openalex.org/W2124592697","https://openalex.org/W2136270365","https://openalex.org/W2145023731","https://openalex.org/W2152772232","https://openalex.org/W2295870555","https://openalex.org/W2339913816","https://openalex.org/W2523632965","https://openalex.org/W2608231518","https://openalex.org/W2611650229","https://openalex.org/W2794990008","https://openalex.org/W2883683269","https://openalex.org/W2888397986","https://openalex.org/W2963881378","https://openalex.org/W4296580612","https://openalex.org/W4298882319","https://openalex.org/W4299366116","https://openalex.org/W6612134913","https://openalex.org/W6631190155","https://openalex.org/W6681151457","https://openalex.org/W6684372118","https://openalex.org/W6738297899","https://openalex.org/W6739651123","https://openalex.org/W6745119210","https://openalex.org/W6746693533","https://openalex.org/W6751554223","https://openalex.org/W6753211666","https://openalex.org/W6842231242"],"related_works":[],"abstract_inverted_index":{"X-Ray":[0,61],"image":[1,8,100],"enhancement,":[2],"along":[3],"with":[4],"many":[5],"other":[6],"medical":[7,45],"processing":[9,101],"applications,":[10],"requires":[11],"the":[12,51,57,113],"segmentation":[13,121],"of":[14,60,87,91,96,115],"images":[15,62],"into":[16],"bone,":[17],"soft":[18],"tissue,":[19],"and":[20,41,55,93,106],"open":[21],"beam":[22],"regions.":[23],"We":[24],"apply":[25],"a":[26],"machine":[27],"learning":[28],"approach":[29],"to":[30,53],"this":[31,129],"problem,":[32],"presenting":[33],"an":[34,71,84,94],"end-to-end":[35,72],"solution":[36,73],"which":[37],"results":[38],"in":[39,122],"robust":[40],"efficient":[42],"inference.":[43],"Since":[44],"institutions":[46],"often":[47],"do":[48],"not":[49],"have":[50],"resources":[52],"process":[54],"label":[56],"large":[58],"quantity":[59],"usually":[63],"needed":[64],"for":[65,74,120,128],"neural":[66,117],"network":[67],"training,":[68],"we":[69],"design":[70],"small":[75],"datasets,":[76],"while":[77,110],"achieving":[78],"state-of-the-art":[79],"results.":[80],"Our":[81],"implementation":[82],"produces":[83],"overall":[85],"accuracy":[86],"92%,":[88],"F1":[89],"score":[90],"0.92,":[92],"AUC":[95],"0.98,":[97],"surpassing":[98],"classical":[99],"techniques,":[102],"such":[103],"as":[104],"clustering":[105],"entropy":[107],"based":[108],"methods,":[109],"improving":[111],"upon":[112],"output":[114],"existing":[116],"networks":[118],"used":[119,127],"non-medical":[123],"contexts.":[124],"The":[125],"code":[126],"project":[130],"is":[131],"available":[132],"online.<sup>1</sup>":[133]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2018-12-11T00:00:00"}