{"id":"https://openalex.org/W7130404931","doi":"https://doi.org/10.1109/tencon66050.2025.11375443","title":"Automated Lung Lesion Segmentation with Minimal Number of Labeled CT Images","display_name":"Automated Lung Lesion Segmentation with Minimal Number of Labeled CT Images","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7130404931","doi":"https://doi.org/10.1109/tencon66050.2025.11375443"},"language":null,"primary_location":{"id":"doi:10.1109/tencon66050.2025.11375443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon66050.2025.11375443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5041419939","display_name":"Ishita Maiti","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ishita Maiti","raw_affiliation_strings":["School of Medical Science and Technology, Indian Institute of Technology Kharagpur,Kharagpur,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Medical Science and Technology, Indian Institute of Technology Kharagpur,Kharagpur,India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126350911","display_name":"Namrata Kadasi","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Namrata Kadasi","raw_affiliation_strings":["Indian Institute of Technology Kharagpur,Electrical Engineering,Kharagpur,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Kharagpur,Electrical Engineering,Kharagpur,India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094010267","display_name":"Nihar Domala","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nihar Domala","raw_affiliation_strings":["IIT Kharagpur,Electrical Engineering,Kharagpur,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Kharagpur,Electrical Engineering,Kharagpur,India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015098367","display_name":"Aman Soni","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aman Soni","raw_affiliation_strings":["Indian Institute of Technology Kharagpur,Electrical Engineering,Kharagpur,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Kharagpur,Electrical Engineering,Kharagpur,India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126336198","display_name":"Manjunatha Mahadevappa","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manjunatha Mahadevappa","raw_affiliation_strings":["School of Medical Science and Technology, Indian Institute of Technology Kharagpur,Kharagpur,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Medical Science and Technology, Indian Institute of Technology Kharagpur,Kharagpur,India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126325293","display_name":"Nirmalya Ghosh","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nirmalya Ghosh","raw_affiliation_strings":["IIT Kharagpur,Electrical Engineering,Kharagpur,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Kharagpur,Electrical Engineering,Kharagpur,India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145894827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.8160415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"723","last_page":"727"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.614300012588501,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.614300012588501,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.12759999930858612,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.04320000112056732,"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/segmentation","display_name":"Segmentation","score":0.7968000173568726},{"id":"https://openalex.org/keywords/lung","display_name":"Lung","score":0.6779000163078308},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.6305999755859375},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5267999768257141},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4986000061035156},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4401000142097473},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4399000108242035}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7968000173568726},{"id":"https://openalex.org/C2777714996","wikidata":"https://www.wikidata.org/wiki/Q7886","display_name":"Lung","level":2,"score":0.6779000163078308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6700999736785889},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.6305999755859375},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5267999768257141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5231999754905701},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4986000061035156},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4401000142097473},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4399000108242035},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3783999979496002},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37040001153945923},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3425999879837036},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3402999937534332},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31929999589920044},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C2781464078","wikidata":"https://www.wikidata.org/wiki/Q7685898","display_name":"Target lesion","level":4,"score":0.2653999924659729}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon66050.2025.11375443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon66050.2025.11375443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2468812405","https://openalex.org/W2774595495","https://openalex.org/W2888493720","https://openalex.org/W2914363005","https://openalex.org/W3027763298","https://openalex.org/W3028070348","https://openalex.org/W3096751066","https://openalex.org/W3112175976","https://openalex.org/W3130010150","https://openalex.org/W3138558221","https://openalex.org/W3139502090","https://openalex.org/W3166931129","https://openalex.org/W4205711607","https://openalex.org/W4206070934","https://openalex.org/W4297860535","https://openalex.org/W4400762160","https://openalex.org/W4401622717"],"related_works":[],"abstract_inverted_index":{"An":[0],"arduous":[1],"task":[2],"in":[3,14,19,45,54,120],"medical":[4],"image":[5,89],"analysis":[6],"is":[7,26,94,127],"the":[8,30,37,67,70,75,121,132,138,183],"automated":[9],"segmentation":[10,21,83,105],"of":[11,22,33,39,64,134,154,167,187,192,198],"infected":[12],"regions":[13,44],"a":[15,142,150],"organ":[16],"(for":[17],"example,":[18],"lungs,":[20],"lung":[23,47,50,76,78,110,158],"lesion),":[24],"which":[25],"crucial":[27],"for":[28,124,157],"assessing":[29],"volumetric":[31],"severity":[32],"infections":[34],"and":[35,60,69,195],"evaluating":[36],"effectiveness":[38],"subsequent":[40],"treatments.":[41],"The":[42,62],"affected":[43],"diseased":[46],"cases,":[48],"called":[49],"lesions,":[51],"vary":[52],"widely":[53],"their":[55],"intensity,":[56],"texture,":[57],"contrast,":[58],"location,":[59],"size.":[61],"similarity":[63],"intensities":[65],"between":[66],"lesion":[68,82,111,159],"healthy":[71],"surrounding":[72],"tissue":[73],"bordering":[74],"makes":[77],"as":[79,81],"well":[80],"more":[84],"challenging,":[85],"especially":[86],"by":[87,113],"classical":[88],"processing":[90],"techniques.":[91],"One":[92],"solution":[93],"machine":[95],"learning":[96,100],"(ML)":[97],"or":[98],"deep":[99],"(DL)-based":[101],"methods,":[102,181],"that":[103,148],"learn":[104],"models":[106],"from":[107,170],"datasets":[108,174],"with":[109,164],"labeled":[112,118,168],"experts.":[114],"Unfortunately,":[115],"acquiring":[116],"any":[117],"data":[119,156,169],"healthcare":[122],"sector":[123],"ML/DL":[125],"algorithms":[126],"prohibitively":[128],"costly":[129],"due":[130],"to":[131,179],"participation":[133],"skilled":[135],"clinicians.":[136],"Hence,":[137],"current":[139],"study":[140],"proposes":[141],"Random":[143],"Forest":[144],"(RF)":[145],"based":[146],"ML-method":[147],"utilizes":[149],"significantly":[151],"reduced":[152],"number":[153],"expert-labeled":[155],"segmentation.":[160],"Eight":[161],"different":[162],"experiments":[163],"varying":[165],"amounts":[166],"two":[171],"challenging":[172],"benchmark":[173],"demonstrated":[175],"encouraging":[176],"results,":[177],"comparable":[178],"state-of-the-art":[180],"reaching":[182],"highest":[184],"precision":[185],"values":[186],"86.4":[188],"%,":[189,194],"recall":[190],"value":[191],"78.1":[193],"F1":[196],"score":[197],"82.0":[199],"%.":[200]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-19T00:00:00"}