{"id":"https://openalex.org/W7126039865","doi":"https://doi.org/10.1109/bibm66473.2025.11357005","title":"MTL-SAM3D: A Multi-Task Learning 3D SAM Framework for 3D MRI Glioma Segmentation and IDH Genotyping","display_name":"MTL-SAM3D: A Multi-Task Learning 3D SAM Framework for 3D MRI Glioma Segmentation and IDH Genotyping","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126039865","doi":"https://doi.org/10.1109/bibm66473.2025.11357005"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5124240012","display_name":"Songhan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Songhan Yang","raw_affiliation_strings":["Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075808879","display_name":"Lufeng Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lufeng Feng","raw_affiliation_strings":["Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025224262","display_name":"Rui Feng","orcid":"https://orcid.org/0000-0003-3052-035X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Feng","raw_affiliation_strings":["Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124167594","display_name":"Han Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han Luo","raw_affiliation_strings":["Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020524854","display_name":"Yue Hu","orcid":"https://orcid.org/0000-0002-7166-4248"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Hu","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology, Joint International Research Laboratory of Silk Road Multilingual Cognitive Computing,Urumqi,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology, Joint International Research Laboratory of Silk Road Multilingual Cognitive Computing,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045637179","display_name":"Jianhong Cheng","orcid":"https://orcid.org/0000-0001-6092-211X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianhong Cheng","raw_affiliation_strings":["Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3118","last_page":"3123"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10129","display_name":"Glioma Diagnosis and Treatment","score":0.5536999702453613,"subfield":{"id":"https://openalex.org/subfields/2716","display_name":"Genetics"},"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/T10129","display_name":"Glioma Diagnosis and Treatment","score":0.5536999702453613,"subfield":{"id":"https://openalex.org/subfields/2716","display_name":"Genetics"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.20029999315738678,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.14970000088214874,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7342000007629395},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.6416000127792358},{"id":"https://openalex.org/keywords/genotyping","display_name":"Genotyping","score":0.6036999821662903},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5392000079154968},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48750001192092896},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4341999888420105},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42260000109672546}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7342000007629395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6976000070571899},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.6416000127792358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6100000143051147},{"id":"https://openalex.org/C31467283","wikidata":"https://www.wikidata.org/wiki/Q912147","display_name":"Genotyping","level":4,"score":0.6036999821662903},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4341999888420105},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42260000109672546},{"id":"https://openalex.org/C2778227246","wikidata":"https://www.wikidata.org/wiki/Q1365309","display_name":"Glioma","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7650036215782166,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G6353568366","display_name":null,"funder_award_id":"62302119","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W3153939879","https://openalex.org/W4205868820","https://openalex.org/W4285553833","https://openalex.org/W4302004698","https://openalex.org/W4311944622","https://openalex.org/W4391109864","https://openalex.org/W4392015811","https://openalex.org/W4392203599","https://openalex.org/W4401638634","https://openalex.org/W4402904115","https://openalex.org/W4403067074","https://openalex.org/W4403961278","https://openalex.org/W4406039681","https://openalex.org/W4408634392","https://openalex.org/W4410838785"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"MRI-based":[1],"glioma":[2,21],"segmentation":[3,22,57,146],"and":[4,14,23,33,80,88,105,157,195],"IDH":[5,24,60,133,159],"genotyping":[6,25,160],"are":[7,129,180],"critical":[8],"for":[9,30],"surgical":[10],"planning,":[11],"prognostic":[12],"assessment,":[13],"therapeutic":[15],"decision-making.":[16],"Existing":[17],"approaches":[18],"typically":[19],"address":[20],"independently,":[26],"requiring":[27],"separate":[28],"models":[29],"each":[31],"task":[32],"thereby":[34],"limiting":[35],"the":[36,76,86,92,111,120,126,132,141,172,177,188],"potential":[37],"benefits":[38],"from":[39],"shared":[40],"representations.":[41],"To":[42],"overcome":[43],"these":[44],"limitations,":[45],"we":[46],"present":[47],"MTL-SAM3D,":[48],"an":[49],"interactive":[50],"multi-task":[51],"framework":[52],"that":[53],"simultaneously":[54],"outputs":[55],"wholetumor":[56],"together":[58],"with":[59,125,148,162],"genotype":[61],"predictions":[62],"while":[63],"remaining":[64],"effective":[65],"on":[66,140,171,182],"unseen":[67],"datasets":[68],"without":[69,185],"any":[70,186],"targetdomain":[71],"fine-tuning.":[72],"The":[73],"design":[74],"freezes":[75],"SAM3D":[77],"image":[78,122],"encoder":[79,102],"inserts":[81],"LoRA":[82],"adapters":[83],"only":[84],"in":[85,203],"query":[87],"value":[89],"projections,":[90],"so":[91],"number":[93],"of":[94,151,154,164,168,193,197],"trainable":[95],"parameters":[96],"stays":[97],"small.":[98],"A":[99],"3D":[100],"prompt":[101],"converts":[103],"point":[104],"mask":[106,112],"prompts":[107],"into":[108],"embeddings.":[109],"Subsequently,":[110],"decoder":[113],"generates":[114],"voxellevel":[115],"tumor":[116],"masks,":[117],"after":[118],"which":[119],"resulting":[121],"features":[123],"along":[124],"predicted":[127],"masks":[128],"aggregated":[130],"by":[131],"classifier":[134],"to":[135],"produce":[136],"case-level":[137],"genotype.":[138],"Trained":[139],"UCSF-PDGM":[142,173],"dataset,":[143],"MTL-SAM3D":[144],"achieves":[145,158],"performance":[147,161],"Dice":[149,192],"score":[150],"0.91,":[152],"HD95":[153],"4.66":[155],"mm,":[156],"AUC":[163,196],"98.34":[165],"%,":[166,199],"accuracy":[167],"95.96":[169],"%":[170],"test":[174],"set.":[175],"When":[176],"same":[178],"weights":[179],"evaluated":[181],"BraTS":[183],"2020":[184],"fine-tuning,":[187],"model":[189],"still":[190],"delivers":[191],"0.82":[194],"88.04":[198],"surpassing":[200],"state-of-the-art":[201],"baselines":[202],"this":[204],"cross-domain":[205],"setting.":[206]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}
