{"id":"https://openalex.org/W3005515008","doi":"https://doi.org/10.1109/bibm47256.2019.8983147","title":"Tumor Segmentation Based on Deeply Supervised Multi-Scale U-Net","display_name":"Tumor Segmentation Based on Deeply Supervised Multi-Scale U-Net","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3005515008","doi":"https://doi.org/10.1109/bibm47256.2019.8983147","mag":"3005515008"},"language":"en","primary_location":{"id":"doi:10.1109/bibm47256.2019.8983147","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5025384190","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-7383-4167"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Key Lab. of Electromagn. Field &amp; Electr. Apparatus Reliability of Hebei Province, Hebei Univ. of Technol., Tianjin, China","Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, China","State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Key Lab. of Electromagn. Field &amp; Electr. Apparatus Reliability of Hebei Province, Hebei Univ. of Technol., Tianjin, China","institution_ids":["https://openalex.org/I184843921"]},{"raw_affiliation_string":"Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, China","institution_ids":["https://openalex.org/I184843921"]},{"raw_affiliation_string":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100408134","display_name":"Bo Wang","orcid":"https://orcid.org/0000-0002-7612-702X"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["Key Lab. of Electromagn. Field &amp; Electr. Apparatus Reliability of Hebei Province, Hebei Univ. of Technol., Tianjin, China","State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, China","Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Key Lab. of Electromagn. Field &amp; Electr. Apparatus Reliability of Hebei Province, Hebei Univ. of Technol., Tianjin, China","institution_ids":["https://openalex.org/I184843921"]},{"raw_affiliation_string":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, China","institution_ids":["https://openalex.org/I184843921"]},{"raw_affiliation_string":"Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022889808","display_name":"Zhenghua Xu","orcid":"https://orcid.org/0000-0002-6719-7333"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenghua Xu","raw_affiliation_strings":["Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology,China","Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology,China","institution_ids":["https://openalex.org/I184843921"]},{"raw_affiliation_string":"Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, China","institution_ids":["https://openalex.org/I184843921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025384190"],"corresponding_institution_ids":["https://openalex.org/I184843921"],"apc_list":null,"apc_paid":null,"fwci":0.2024,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.56584244,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"746","last_page":"749"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9990000128746033,"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":0.9980999827384949,"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/segmentation","display_name":"Segmentation","score":0.7815690636634827},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.734645426273346},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7276814579963684},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6779178977012634},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6752756237983704},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6076531410217285},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5640550851821899},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5458313822746277},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4778863191604614},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4767685532569885},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41186076402664185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3979445993900299},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3715609908103943},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14236676692962646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0951952338218689}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7815690636634827},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.734645426273346},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7276814579963684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6779178977012634},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6752756237983704},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6076531410217285},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5640550851821899},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5458313822746277},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4778863191604614},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4767685532569885},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41186076402664185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3979445993900299},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3715609908103943},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14236676692962646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0951952338218689},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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":1,"locations":[{"id":"doi:10.1109/bibm47256.2019.8983147","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1745334888","https://openalex.org/W1799366690","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2097117768","https://openalex.org/W2101608218","https://openalex.org/W2109255472","https://openalex.org/W2471801048","https://openalex.org/W2517954747","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2589644515","https://openalex.org/W2622064152","https://openalex.org/W2705158815","https://openalex.org/W2884436604","https://openalex.org/W2887113336","https://openalex.org/W3101639073","https://openalex.org/W6639824700"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W2022929107","https://openalex.org/W2055202857","https://openalex.org/W80586315","https://openalex.org/W4205800335","https://openalex.org/W2758994127"],"abstract_inverted_index":{"Although":[0],"deep":[1,16],"learning":[2,17],"has":[3,91],"achieved":[4],"great":[5],"success":[6],"in":[7],"the":[8,14,67,86,97],"field":[9],"of":[10],"medical":[11,19],"image":[12,20],"processing,":[13],"existing":[15,68],"based":[18],"segmentation":[21,57,94],"solutions":[22],"still":[23],"cannot":[24],"obtain":[25],"satisfactory":[26],"performances":[27,58,95],"for":[28,54],"abdominal":[29,60],"small":[30,37,61],"organs":[31,62],"and":[32,40,76],"lesions":[33],"due":[34],"to":[35],"their":[36],"object":[38],"size":[39],"shape-variability.":[41],"In":[42],"this":[43],"work,":[44],"a":[45,72],"Deeply":[46],"Supervised":[47],"Multi-Scale":[48],"U-Net":[49,65,69,89],"(DSMS":[50],"U-Net)":[51],"is":[52],"proposed":[53,87],"more":[55],"accurate":[56],"on":[59],"images.":[63],"DSMS":[64,88],"integrate":[66],"model":[70],"with":[71],"restoration":[73],"decoder":[74],"module":[75],"some":[77],"multi-scale":[78],"convolution":[79],"modules.":[80],"Our":[81],"experiment":[82],"results":[83],"demonstrate":[84],"that":[85],"approach":[90],"much":[92],"better":[93],"than":[96],"state-of-the-art":[98],"baselines.":[99]},"counts_by_year":[{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
