Research map: Multimodal Radiomics Combined with Habitat Analysis for Precise Preoperative Differentiation of WHO Grade I Meningioma Subtypes

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  1. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation · Fabian Isensee · 2020 · 9720 citations · Cited by this paper
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  11. Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging · Yae Won Park · 2018 · 182 citations · Cited by this paper
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  13. Radiographic prediction of meningioma grade by semantic and radiomic features · Thibaud P. Coroller · 2017 · 155 citations · Cited by this paper
  14. Investigating the Association Between Carotid Atherosclerotic Plaque Characteristics And Lacunar Infarction Using High-Resolution Vessel Wall Imaging · 2026 · Related
  15. Multiplatform genomic profiling and magnetic resonance imaging identify mechanisms underlying intratumor heterogeneity in meningioma · Stephen T. Magill · 2020 · 133 citations · Cited by this paper
  16. Development and Internal Validation of a Nomogram Model Discriminating Liver Metastases of Melanoma From Other Common Liver Metastases Based on the Combination of Conventional Ultrasonography and Contrast-enhanced Ultrasonography · 2026 · Related
  17. WHO grade, proliferation index, and progesterone receptor expression are different according to the location of meningioma · Francesco Maiuri · 2019 · 75 citations · Cited by this paper
  18. Multimodal Imaging of Tau Pathology and Network Connectivity Dynamics Across the Alzheimer’s Continuum: A Pilot Study Using Second-Generation Tracer [18F]MK6240 · 2026 · Related
  19. Accuracy of Radiomics-Based Feature Analysis on Multiparametric Magnetic Resonance Images for Noninvasive Meningioma Grading · Kai Roman Laukamp · 2019 · 72 citations · Cited by this paper
  20. Radiologist-Informed Radiomics: Improving the Accuracy of Preoperative Assessment for Lymph Node Metastasis in Rectal Cancer · 2026 · Related
  21. Differentiation Researches on the Meningioma Subtypes by Radiomics from Contrast-Enhanced Magnetic Resonance Imaging: A Preliminary Study · Lei Niu · 2019 · 50 citations · Cited by this paper
  22. Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation · Ling Wu · 2025 · 41 citations · Cited by this paper
  23. Meningioma grading using conventional MRI histogram analysis based on 3D tumor measurement · Xiaoxin Li · 2018 · 40 citations · Cited by this paper
  24. WHO grade I meningioma subtypes: MRI features and pathological analysis · Tao Zhang · 2018 · 38 citations · Cited by this paper
  25. Application of radiomics to meningiomas: A systematic review · Ruchit V. Patel · 2023 · 30 citations · Cited by this paper
  26. Quality assessment of meningioma radiomics studies: Bridging the gap between exploratory research and clinical applications · So Yeon Won · 2021 · 28 citations · Cited by this paper
  27. Meningioma Radiomics: At the Nexus of Imaging, Pathology and Biomolecular Characterization · Lorenzo Ugga · 2022 · 28 citations · Cited by this paper
  28. Use of advanced neuroimaging and artificial intelligence in meningiomas · Norbert Galldiks · 2022 · 24 citations · Cited by this paper
  29. Biomarkers for differentiating grade II meningiomas from grade I: a systematic review · Agbolahan A. Sofela · 2021 · 17 citations · Cited by this paper
  30. Occurrence of Fibrotic Tumor Vessels in Grade I Meningiomas Is Strongly Associated with Vessel Density, Expression of VEGF, PlGF, IGFBP-3 and Tumor Recurrence · Katharina Heß · 2020 · 16 citations · Cited by this paper
  31. A Machine Learning Model Based on Unsupervised Clustering Multihabitat to Predict the Pathological Grading of Meningiomas · Xinghao Wang · 2022 · 8 citations · Cited by this paper
  32. Multimodal deep learning-based radiomics for meningioma consistency prediction: integrating T1 and T2 MRI in a multi-center study · Huanjie Lin · 2025 · 4 citations · Cited by this paper
  33. Multisequence magnetic resonance imaging habitat analysis for pre-operative meningioma grade prediction · Zongyou Cai · 2025 · 2 citations · Cited by this paper

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