{"id":"https://openalex.org/W4404788881","doi":"https://doi.org/10.1109/tsmc.2024.3489029","title":"Weighted Deformable Network for Efficient Segmentation of Lung Tumors in CT","display_name":"Weighted Deformable Network for Efficient Segmentation of Lung Tumors in CT","publication_year":2024,"publication_date":"2024-11-27","ids":{"openalex":"https://openalex.org/W4404788881","doi":"https://doi.org/10.1109/tsmc.2024.3489029"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2024.3489029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2024.3489029","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-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/A5018310642","display_name":"Surochita Pal","orcid":null},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Surochita Pal","raw_affiliation_strings":["Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028039397","display_name":"Sushmita Mitra","orcid":"https://orcid.org/0000-0001-9285-1117"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sushmita Mitra","raw_affiliation_strings":["Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072419176","display_name":"B. Uma Shankar","orcid":null},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. Uma Shankar","raw_affiliation_strings":["Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018310642"],"corresponding_institution_ids":["https://openalex.org/I6498739"],"apc_list":null,"apc_paid":null,"fwci":1.292,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.81916097,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"55","issue":"2","first_page":"898","last_page":"909"},"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":0.982699990272522,"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":0.982699990272522,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9682999849319458,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.942300021648407,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5074102282524109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43610015511512756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39238959550857544},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.39211517572402954},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.32223182916641235}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5074102282524109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43610015511512756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39238959550857544},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.39211517572402954},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.32223182916641235}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsmc.2024.3489029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2024.3489029","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1978068592","https://openalex.org/W1986649315","https://openalex.org/W2015398848","https://openalex.org/W2040033900","https://openalex.org/W2052507258","https://openalex.org/W2103004421","https://openalex.org/W2110723426","https://openalex.org/W2124932867","https://openalex.org/W2225538867","https://openalex.org/W2466033276","https://openalex.org/W2535300095","https://openalex.org/W2587530497","https://openalex.org/W2601564443","https://openalex.org/W2883311907","https://openalex.org/W2884561390","https://openalex.org/W2896246551","https://openalex.org/W2903617078","https://openalex.org/W2928133111","https://openalex.org/W2946185430","https://openalex.org/W2962767316","https://openalex.org/W2996290406","https://openalex.org/W3007192987","https://openalex.org/W3026701342","https://openalex.org/W3037120822","https://openalex.org/W3045605181","https://openalex.org/W3092817666","https://openalex.org/W3129430687","https://openalex.org/W3130794141","https://openalex.org/W3138516171","https://openalex.org/W3164581645","https://openalex.org/W3172681723","https://openalex.org/W3186852274","https://openalex.org/W3214813820","https://openalex.org/W4200082766","https://openalex.org/W4225849231","https://openalex.org/W4281760791","https://openalex.org/W4291730167","https://openalex.org/W4295004920","https://openalex.org/W4309297183","https://openalex.org/W4312337217","https://openalex.org/W4378715432","https://openalex.org/W4385820084","https://openalex.org/W4386567710","https://openalex.org/W4392888317","https://openalex.org/W4394596865","https://openalex.org/W4403067091","https://openalex.org/W6631190155","https://openalex.org/W6860915106"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3031052312","https://openalex.org/W4389568370","https://openalex.org/W3032375762","https://openalex.org/W1995515455","https://openalex.org/W2080531066","https://openalex.org/W3108674512","https://openalex.org/W1506200166"],"abstract_inverted_index":{"The":[0],"computerized":[1],"delineation":[2,71,96],"and":[3,26,50,72,148,195],"prognosis":[4],"of":[5,20,45,47,53,56,77,97,113,115,157,186,193,205],"lung":[6,48,167,177],"cancer":[7,49,168],"is":[8,23,118],"typically":[9],"based":[10],"on":[11,163,174],"Computed":[12],"Tomography":[13],"(CT)":[14],"image":[15,38],"analysis,":[16],"whereby":[17],"the":[18,42,51,61,75,88,98,103,121,155,175,188,198],"region":[19,114],"interest":[21],"(ROI)":[22],"accurately":[24],"demarcated":[25],"classified.":[27],"Deep":[28],"learning":[29],"in":[30],"computer":[31],"vision":[32],"provides":[33],"a":[34],"different":[35],"perspective":[36],"to":[37,41,126],"segmentation.":[39],"Due":[40],"increasing":[43],"number":[44],"cases":[46],"availability":[52],"large":[54],"volumes":[55],"CT":[57],"scans":[58],"every":[59],"day,":[60],"need":[62],"for":[63,80,94],"automated":[64],"handling":[65],"becomes":[66],"imperative.":[67],"This":[68,117],"requires":[69],"efficient":[70,95],"diagnosis":[73],"through":[74],"design":[76],"new":[78,135],"techniques":[79],"improved":[81],"accuracy.":[82],"In":[83],"this":[84],"article,":[85],"we":[86],"introduce":[87],"novel":[89],"Weighted":[90],"Deformable":[91,104],"U-Net":[92],"(WDU-Net)":[93],"tumor":[99,178],"region.":[100],"It":[101],"incorporates":[102],"Convolution":[105],"(DC)":[106],"that":[107],"can":[108],"model":[109],"arbitrary":[110],"geometric":[111],"shapes":[112],"interests.":[116],"enhanced":[119],"by":[120],"Weight":[122],"Generation":[123],"(WG)":[124],"module":[125],"suppress":[127],"unimportant":[128],"features":[129],"while":[130],"highlighting":[131],"relevant":[132],"ones.":[133],"A":[134],"Focal":[136],"Asymmetric":[137],"Similarity":[138],"(FAS)":[139],"loss":[140],"function":[141],"helps":[142],"handle":[143],"class":[144],"imbalance.":[145],"Ablation":[146],"studies":[147],"comparison":[149],"with":[150,159,181],"state-of-the-art":[151],"models":[152],"help":[153],"establish":[154],"effectiveness":[156],"WDU-Net":[158],"ensemble":[160],"learning,":[161],"tested":[162],"five":[164],"publicly":[165],"available":[166],"datasets.":[169],"Best":[170],"results":[171],"were":[172],"obtained":[173],"LIDC-IDRI":[176],"test":[179],"dataset,":[180],"an":[182],"average":[183],"Dice":[184],"score":[185],"0.9137,":[187],"Hausdorff":[189],"Distance":[190],"95%":[191],"(HD95)":[192],"5.3852,":[194],"Area":[196],"Under":[197],"Receiver":[199],"Operating":[200],"Characteristic":[201],"(ROC)":[202],"Curve":[203],"(AUC)":[204],"0.9449.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}