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However, existing point\u2010based deep learning methods suffer from limited feature representation and poor segmentation performance on medical data due to insufficient training samples and complex geometric variations. M\u2010PointNet introduces a novel multi\u2010layer embedded deep learning architecture that significantly enhances the classification and segmentation of intracranial aneurysms through three key innovations: (1) an enhanced PointNet++ with an expanded hierarchical structure for better geometric feature extraction; (2) a multi\u2010layer embedding mechanism that integrates preprocessed and resampled point cloud data at multiple hierarchical levels to enrich feature representation; and (3) a deep supervision strategy with auxiliary output layers to accelerate convergence and improve performance. Experiments on the IntrA dataset demonstrate that M\u2010PointNet achieves 91.96% accuracy and a 0.923 F1\u2010score in classification, surpassing baseline by 5.27% and 3.0%, respectively. For segmentation, it attains 83.85% IoU and 90.25% DSC for aneurysm regions and 95.81% IoU and 97.82% DSC for vessel regions. Additionally, its generalization capability is validated by a 92.8% accuracy on the ModelNet40 dataset. M\u2010PointNet effectively addresses the challenges of medical point cloud analysis, achieving state\u2010of\u2010the\u2010art performance in intracranial aneurysms classification and segmentation while maintaining robust cross\u2010domain\u00a0generalization.<\/jats:p>","DOI":"10.1049\/ipr2.70275","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T14:41:25Z","timestamp":1767624085000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["M\u2010PointNet: A Multi\u2010Layer Embedded Deep Learning Model for 3D Intracranial Aneurysm Classification and Segmentation"],"prefix":"10.1049","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0547-5219","authenticated-orcid":false,"given":"Jiaqi","family":"Wang","sequence":"first","affiliation":[{"name":"Medical Information School Wannan Medical College Wuhu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juntong","family":"Liu","sequence":"additional","affiliation":[{"name":"Medical Information School Wannan Medical College Wuhu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengyuan","family":"Xu","sequence":"additional","affiliation":[{"name":"Medical Imaging School Wannan Medical College Wuhu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunfeng","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital of Wannan Medical College Wuhu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingquan","family":"Ye","sequence":"additional","affiliation":[{"name":"Medical Information School Wannan Medical College Wuhu China"},{"name":"Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"265","published-online":{"date-parts":[[2026,1,5]]},"reference":[{"issue":"4","key":"e_1_2_12_2_1","doi-asserted-by":"crossref","first-page":"1957","DOI":"10.1007\/s41870-024-02292-0","article-title":"Intelligent Computational Ensemble Model for Predicting Cerebral Aneurysm Using the Concept of Region Localization in Multi\u2010Section CT Angiography","volume":"17","author":"Khan Z.","year":"2025","journal-title":"International Journal of Information Technology"},{"issue":"1","key":"e_1_2_12_3_1","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1007\/s00701-025-06469-9","article-title":"Fast Simulation of Hemodynamics in Intracranial Aneurysms for Clinical Use","volume":"167","author":"Deuter D.","year":"2025","journal-title":"Acta Neurochirurgica"},{"issue":"1","key":"e_1_2_12_4_1","first-page":"1","article-title":"Evaluating Artificial Intelligence Models for Rupture Risk Prediction in Unruptured Intracranial Aneurysms: A Focus On Vessel Geometry and Hemodynamic Insights","volume":"48","author":"Khan M. 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