{"id":"https://openalex.org/W7118186426","doi":"https://doi.org/10.1049/ipr2.70275","title":"M\u2010PointNet: A Multi\u2010Layer Embedded Deep Learning Model for 3D Intracranial Aneurysm Classification and Segmentation","display_name":"M\u2010PointNet: A Multi\u2010Layer Embedded Deep Learning Model for 3D Intracranial Aneurysm Classification and Segmentation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7118186426","doi":"https://doi.org/10.1049/ipr2.70275"},"language":"en","primary_location":{"id":"doi:10.1049/ipr2.70275","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70275","pdf_url":null,"source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1049/ipr2.70275","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jiaqi Wang","orcid":"https://orcid.org/0000-0003-0547-5219"},"institutions":[{"id":"https://openalex.org/I100357981","display_name":"Wannan Medical College","ror":"https://ror.org/037ejjy86","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I100357981"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Wang","raw_affiliation_strings":["Medical Information School Wannan Medical College Wuhu China"],"raw_orcid":"https://orcid.org/0000-0003-0547-5219","affiliations":[{"raw_affiliation_string":"Medical Information School Wannan Medical College Wuhu China","institution_ids":["https://openalex.org/I100357981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121927916","display_name":"Juntong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I100357981","display_name":"Wannan Medical College","ror":"https://ror.org/037ejjy86","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I100357981"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juntong Liu","raw_affiliation_strings":["Medical Information School Wannan Medical College Wuhu China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical Information School Wannan Medical College Wuhu China","institution_ids":["https://openalex.org/I100357981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121948324","display_name":"Zhengyuan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I100357981","display_name":"Wannan Medical College","ror":"https://ror.org/037ejjy86","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I100357981"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyuan Xu","raw_affiliation_strings":["Medical Imaging School Wannan Medical College Wuhu China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical Imaging School Wannan Medical College Wuhu China","institution_ids":["https://openalex.org/I100357981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101858640","display_name":"Yunfeng Zhou","orcid":"https://orcid.org/0000-0001-5260-3071"},"institutions":[{"id":"https://openalex.org/I4210167381","display_name":"First Affiliated Hospital of Wannan Medical College","ror":"https://ror.org/05wbpaf14","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210167381"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunfeng Zhou","raw_affiliation_strings":["Department of Radiology The First Affiliated Hospital of Wannan Medical College Wuhu China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology The First Affiliated Hospital of Wannan Medical College Wuhu China","institution_ids":["https://openalex.org/I4210167381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101870866","display_name":"Mingquan Ye","orcid":"https://orcid.org/0009-0007-8474-4910"},"institutions":[{"id":"https://openalex.org/I100357981","display_name":"Wannan Medical College","ror":"https://ror.org/037ejjy86","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I100357981"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingquan Ye","raw_affiliation_strings":["Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China","Medical Information School Wannan Medical College Wuhu China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China","institution_ids":[]},{"raw_affiliation_string":"Medical Information School Wannan Medical College Wuhu China","institution_ids":["https://openalex.org/I100357981"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101858640","https://openalex.org/A5101870866"],"corresponding_institution_ids":["https://openalex.org/I100357981","https://openalex.org/I4210167381"],"apc_list":{"value":2530,"currency":"USD","value_usd":2530},"apc_paid":{"value":2530,"currency":"USD","value_usd":2530},"fwci":25.7011,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.992731,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"20","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10420","display_name":"Intracranial Aneurysms: Treatment and Complications","score":0.9075999855995178,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/T10420","display_name":"Intracranial Aneurysms: Treatment and Complications","score":0.9075999855995178,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.01360000018030405,"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":0.006099999882280827,"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/point-cloud","display_name":"Point cloud","score":0.7781000137329102},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7595000267028809},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7491000294685364},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6133000254631042},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.545199990272522},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5295000076293945},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.476500004529953},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4562999904155731},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3977000117301941}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8396000266075134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8083999752998352},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7781000137329102},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7595000267028809},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7491000294685364},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6133000254631042},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5295000076293945},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4562999904155731},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3977000117301941},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38040000200271606},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27570000290870667},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.2526000142097473},{"id":"https://openalex.org/C195958017","wikidata":"https://www.wikidata.org/wiki/Q1675268","display_name":"Iterative closest point","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1049/ipr2.70275","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70275","pdf_url":null,"source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1049/ipr2.70275","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70275","pdf_url":null,"source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W1990517717","https://openalex.org/W2144491133","https://openalex.org/W2211722331","https://openalex.org/W2464708700","https://openalex.org/W2502206489","https://openalex.org/W2782364420","https://openalex.org/W2797997528","https://openalex.org/W2806332096","https://openalex.org/W2895926594","https://openalex.org/W2903291548","https://openalex.org/W2904807675","https://openalex.org/W2962731536","https://openalex.org/W2963158438","https://openalex.org/W2963231572","https://openalex.org/W2963719584","https://openalex.org/W2964253930","https://openalex.org/W2979750740","https://openalex.org/W3011730771","https://openalex.org/W3012280898","https://openalex.org/W3035168834","https://openalex.org/W3108194527","https://openalex.org/W3111535274","https://openalex.org/W3196757234","https://openalex.org/W4212819272","https://openalex.org/W4214755140","https://openalex.org/W4221138247","https://openalex.org/W4223459101","https://openalex.org/W4291910375","https://openalex.org/W4362547092","https://openalex.org/W4385880767","https://openalex.org/W4390503071","https://openalex.org/W4399310824","https://openalex.org/W4403839092","https://openalex.org/W4406848097","https://openalex.org/W4407127714","https://openalex.org/W4408101878","https://openalex.org/W4408951610","https://openalex.org/W4409262773","https://openalex.org/W4409886519"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"Accurate":[1],"classification":[2,61,197],"and":[3,18,32,44,62,93,106,119,133,143,152,158,161,198],"segmentation":[4,34,63,199],"of":[5,64,186],"intracranial":[6,65,195],"aneurysms":[7,66,196],"from":[8,28],"3D":[9],"point":[10,95,188],"cloud":[11,96,189],"data":[12,38,97],"are":[13],"critical":[14],"for":[15,80,155,164],"computer\u2010aided":[16],"diagnosis":[17],"surgical":[19],"planning.":[20],"However,":[21],"existing":[22],"point\u2010based":[23],"deep":[24,54,109],"learning":[25,55],"methods":[26],"suffer":[27],"limited":[29],"feature":[30,83,104],"representation":[31],"poor":[33],"performance":[35,193],"on":[36,123,177],"medical":[37,187],"due":[39],"to":[40,102,116],"insufficient":[41],"training":[42],"samples":[43],"complex":[45],"geometric":[46,82],"variations.":[47],"M\u2010PointNet":[48,129,181],"introduces":[49],"a":[50,86,108,134,174],"novel":[51],"multi\u2010layer":[52,87],"embedded":[53],"architecture":[56],"that":[57,90,128],"significantly":[58],"enhances":[59],"the":[60,124,178,184],"through":[67],"three":[68],"key":[69],"innovations:":[70],"(1)":[71],"an":[72,76],"enhanced":[73],"PointNet++":[74],"with":[75,112],"expanded":[77],"hierarchical":[78,100],"structure":[79],"better":[81],"extraction;":[84],"(2)":[85],"embedding":[88],"mechanism":[89],"integrates":[91],"preprocessed":[92],"resampled":[94],"at":[98],"multiple":[99],"levels":[101],"enrich":[103],"representation;":[105],"(3)":[107],"supervision":[110],"strategy":[111],"auxiliary":[113],"output":[114],"layers":[115],"accelerate":[117],"convergence":[118],"improve":[120],"performance.":[121],"Experiments":[122],"IntrA":[125],"dataset":[126],"demonstrate":[127],"achieves":[130],"91.96%":[131],"accuracy":[132,176],"0.923":[135],"F1\u2010score":[136],"in":[137,194],"classification,":[138],"surpassing":[139],"baseline":[140],"by":[141,173],"5.27%":[142],"3.0%,":[144],"respectively.":[145],"For":[146],"segmentation,":[147],"it":[148],"attains":[149],"83.85%":[150],"IoU":[151,160],"90.25%":[153],"DSC":[154,163],"aneurysm":[156],"regions":[157],"95.81%":[159],"97.82%":[162],"vessel":[165],"regions.":[166],"Additionally,":[167],"its":[168],"generalization":[169],"capability":[170],"is":[171],"validated":[172],"92.8%":[175],"ModelNet40":[179],"dataset.":[180],"effectively":[182],"addresses":[183],"challenges":[185],"analysis,":[190],"achieving":[191],"state\u2010of\u2010the\u2010art":[192],"while":[200],"maintaining":[201],"robust":[202],"cross\u2010domain":[203],"generalization.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-01-05T00:00:00"}
