Brain Tumor Classification

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Overview

Brain tumor classification assigns tumor type, grade, or molecular subtype from MRI, histopathology, molecular assays, and sometimes clinical or longitudinal data to support diagnosis and treatment planning. Approaches range from CNNs and vision transformers on MRI to radiomics, shape and topology features, whole-slide learning, and multimodal fusion; self-supervised and transfer learning help address limited labels. Work spans public image benchmarks such as BraTS and BRISC as well as biopsy-linked and multi-center cohorts, with systems also tackling recurrence versus treatment effects and adding uncertainty estimates or visual explanations. A central challenge is whether benchmark performance generalizes across hospitals and missing modalities: data leakage, acquisition shifts, class imbalance, and uncertain gains from synthetic data make patient-disjoint and external validation essential.

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51 papers6 papers in the last four weeks, up 50% on the four weeks before. 0.0% of all new papers.

  1. The Federated Tumor Segmentation and Classification (FeTS++) Challenge

    Oct 13, 2026Wenyi Tang, Carla Pitarch-Abaigar, Siddhesh Thakur +5Medical Image SegmentationMedical Image Benchmarks

    Research Center for Federated Learning in Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. · Division of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. · Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA. +5

  2. AI-Enhanced Hyperspectral Imaging for Intraoperative Detection of Low-Grade Glioma: A Clinical Study

    Oct 13, 2026Siri Willems, Ishika Jain, Jens De Winne +9Brain Tumor ClassificationHyperspectral Imaging

    imec, Kapeldreef 75, Leuven, 3001, Belgium · Department of Computer Science UAntwerp-imec, Sint-Pietersvliet 7, Antwerp, 2000, Belgium · Department of Telecommunications and Information Processing, IPI-imec, Sint-Pietersnieuwestraat 41, Ghent, 9000, Belgium +3

  3. BrainAid: Efficient Brain Tumor Detection Using Lightweight CNNs and Explainable AI for Resource-Constrained Environments

    Oct 10, 2026Sai Sriram Gonthina, Ross Gore, Bikash Chandra Singh +4Lightweight Neural NetworksBrain Tumor Classification

    Department of Computer Science and Engineering, IIIT - Naya Raipur, Raipur, Chhattisgarh, India · Center for Secure & Intelligent Critical Systems, Old Dominion University, Virginia, USA · Department of Computer Science, California State University, Fresno, USA +2

  4. STRIDE: Spatial-Temporal Representation for Interval-conditioned Disease Evolution in Longitudinal Glioblastoma MRI

    Oct 2, 2026Wenhao Guo, Changchang Yin, Pierre Giglio +3Longitudinal Medical Image AnalysisMedical Image Representation Learning

    Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA · Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA · Department of Neurology, The Ohio State University, Columbus, OH, USA

  5. Scores That Hold, Benchmarks That Leak: Measuring Dataset Contamination in Public Brain-Tumor MRI Classification

    Sep 30, 2026Bhanu Prakash Vangala, Sowmya Guda, Latha Peddi +1Data LeakageBenchmark Contamination

    Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211 USA · Government Degree College (Autonomous), Siddipet, Telangana 502103, India · Amar Biotech Private Limited, Kondapur, Hyderabad, Telangana 500084, India

  6. Towards Trustworthy AI for Glioma Diagnosis: A Task-Aware Evaluation of Uncertainty Quantification

    Sep 30, 2026Gonzalo Esteban Mosquera Rojas, Sebastian R. van der Voort, Carolin M. Pirkl +3Uncertainty QuantificationBrain Tumor Classification

    Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands · Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands · GE HealthCare, Munich, Germany +3

  7. Evaluating Single and Multi-Omics Based Explainable Artificial Intelligence (MOXAI) for Molecular Subclass Classification of Adult-Type Diffuse Gliomas

    Sep 26, 2026Md Zahangir Alom, Quynh T. Tran, Breuer Alexandar +1Multi-Omics Data IntegrationBrain Tumor Classification

    Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN 38105 USA.

  8. Does DCGAN-Based Synthetic Augmentation Improve Brain Tumor MRI Classification? An Empirical Study

    Sep 20, 2026Irhum Jawad Khan, Talha bin AslamSynthetic Data AugmentationMedical Image Classification

    School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad, Pakistan · Independent Researcher Islamabad, Pakistan

  9. A Vision-Language Foundation Model for Precise and Comprehensive Brain Tumor Diagnosis from Preoperative Multimodal Data

    Sep 15, 2026Yinong Wang, Jianwen Chen, Zhou Chen +28Medical VLMsBrain Tumor Classification

    Joyce · Department of Neurosurgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, China · Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, China +19

  10. The Diagnosis a Reporter Leaves Unspoken: Surfacing Frozen Tumor Features for Brain-Tumor MRI Reporting

    Sep 2, 2026Khawaja Murad ul Hassan, Ruqiyya Adil, Adil Qayyum +4Radiology Report GenerationBrain MRI

    National University of Sciences and Technology, Islamabad, Pakistan · Consultant Radiologist, Rawalpindi, Pakistan · Bahria University Health Sciences Campus, Islamabad, Pakistan +1

  11. Heterogeneity-Aware Deep Learning for Tumour Classification from Multiparametric MRI

    Aug 18, 2026Yue Xia, Euijoon Ahn, Tian Xia +3Medical Image ClassificationOncology

    School of Computer Science, The University of Sydney, Camperdown, NSW, 2006, Australia. · Department of Molecular Imaging, Royal Prince Alfred Hospital, Camperdown, NSW, 2006, Australia.

  12. NeuroMosaic: Anatomically Grounded Multimodal Large Language Modeling for Molecularly Aware Glioma Reasoning from 3D MRI and Clinical Narratives

    Aug 4, 2026Yantong Liu, Zheyu Zhang, Runpeng Liu +3Multimodal Large Language ModelsMedical VLMs

    Department of Computer Information Engineering, Kunsan National University, Gunsan 54150, Republic of Korea · School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China

  13. DS@GT ARC at MEDIQA-CORE-Task-1 2026: Trimodal Model Fusion with Task-Specific Gates for Brain Tumor Subtype Classification

    Jul 30, 2026Hoang Thanh Thanh Truong, Charles R. ClarkMultimodal ClassificationBrain Tumor Classification

    Georgia Institute of Technology, North Ave NW, Atlanta, GA 30332 · University of Florida, Stadium Rd, Gainesville, FL 32611

  14. Shape-Based Inductive Bias for Glioma Grading from Tumor Contours

    Jul 27, 2026Puneet Velidi, Michelle F. Miranda, Farouk Nathoo +2BraTSGeometric Representation Learning

    Department of Mathematics and Statistics University of Victoria · Department of Computer Science University of Victoria · D´epartement de math´ematiques Universit´e du Qu´ebec `a Montr´eal

  15. TVT-PAPD: Pathology-Aware Prototype Distillation for Self-Supervised Whole Slide Image Classification

    Jul 11, 2026Ramesh Naidu Laveti, Jaya Sreevalsan-Nair, T K SrikanthPrototype LearningHistopathology Image Classification

    E-Health Research Center, International Institute of Information Technology Bangalore, Karnataka 560100, India.

  16. Generative Augmentation of Raman Spectra for Glioma Classification

    Jul 11, 2026Andrei Iuşan, Iulian Vasile, Daria Voiculescu +4Synthetic Data AugmentationRaman Spectroscopy

    National Institute of Research and Development for Biological Sciences, Romania · Department of Mathematics and Statistics, University of Turku, Finland · Research Institute for Artificial Intelligence “Mihai Dragănescu”, Romanian Academy +2

  17. A Novel Machine Learning Approach for Central Nervous System Tumor Classification from DNA Methylation

    Jul 1, 2026Paulo R. Ferreira, Lucas Coutinho Freitas, Laís dos Santos Gonçalves +4Multiclass ClassificationOncology

    Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil · Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil

  18. Automated brain tumor detection in MRI images using CNN and ResNet architectures

    Jun 25, 2026Annapurna V K, Asha N, K Paramesha +2Convolutional Neural NetworksBrain Tumor Classification

    Department of Computer Science and Engineering, The National Institute of Engineering, Mysuru, Karnataka, India. · Department of MCA, The National Institute of Engineering, Mysuru, Karnataka, India. · Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, Karnataka, India. +1

  19. Multi-cancer detection using a computationally efficient CNN with transfer learning

    Jun 21, 2026Vasileios E. Papageorgiou, Georgios Petmezas, Dimitrios-Panagiotis Papageorgiou +2Efficient Neural Network InferenceMedical Image Classification

    School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece · Department of Mathematics, National and Kapodistrian University of Athens, Athens, Greece · Department of Mathematics, Aristotle University of Thessaloniki, Thessaloniki, Greece +1

  20. Multi-Class Brain Tumor Classification Using Advanced Deep Learning Models: A Comparative Study

    Jun 17, 2026Asad Channa, Asghar Ali Chandio, Akhtar Hussain Jalbani +2Medical Image ClassificationMulticlass Classification

    Department of Computer Science, Quaid-e-Awam University of Engineering, Sciences & Technology, Paksitan · Department of Artificial Intelligence, Quaid-e-Awam University of Engineering, Sciences & Technology, Pakistan · The Faculty of Artificial Intelligence and Cyber Security, Universiti Teknikal Malaysia Melaka +2

  21. BrainFusionNet: a deep learning and XAI model to understand local, global, and sequential features of MRI images for improved brain tumour detection

    Jun 17, 2026Md Taimur Ahad, Bo Song, Yan LiHybrid CNN-Transformer ArchitecturesExplainable Medical Image Analysis

    School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, QLD 4350, Australia · School of Engineering, University of Southern Queensland, Toowoomba, QLD 4350, Australia

  22. Multimodal Brain Tumour Classification Using Feature Fusion

    Jun 9, 2026Wajih ul Islam, Muhammad Yaqoob, Javed Ali Khan +1Multimodal ClassificationMedical Image Classification

    School of Physics, Engineering and Computer Science, University of Hertfordshire, UK

  23. Bridging Topology and Deep Representation Learning: A TDA-ViT Fusion Model for Four-Class Brain Tumor Classification

    May 30, 2026Faisal AhmedVision TransformerMedical Image Classification

    Department of Data Science and Mathematics, Embry-Riddle Aeronautical University, 3700 Willow Creek Rd, Prescott, 86301, Arizona, USA.

  24. ConceptM3^3oE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology

    May 23, 2026Xuan Wang, Zhongling Xu, Gopi Kannedhara +13Computational PathologyConcept Bottleneck Models

    University of Texas at Austin, Austin, TX, USA · University of North Carolina at Chapel Hill, NC, USA · Dell Children’s Medical Center, Austin, TX, USA +2

  25. Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025

    May 21, 2026José Rafael Noriega CedeñoSynthetic Data AugmentationMedical Image Classification

    Faculty of Applied Sciences and Technology

  26. Quantized Machine Learning Models for Medical Imaging in Low-Resource Healthcare Settings

    May 19, 2026Sumanth Meenan Kanneti, Aryan ShahEfficient Neural Network InferenceMedical Image Classification

    Georgia State University · University of Southern California

  27. Brain Tumor Classification in MRI Images: A Computationally Efficient Convolutional Neural Network

    May 11, 2026Md Fahimul Kabir Chowdhury, Jannatul FerdousEfficient Neural Network InferenceMedical Image Classification

    Department of Computer Science and Engineering, University of North Texas, USA · Department of Electrical and Electronic Engineering, International Islamic University Chittagong, Bangladesh

  28. Bridging visual saliency and large language models for explainable deep learning in medical imaging

    May 7, 2026Paul Valery Nguezet, Elie Tagne Fute, Yusuf Brima +2Radiology Report GenerationMedical Image Classification

    Department of Mathematics and Computer science, University of Dschang, Dschang, 67, Cameroon. · Computer Vision, Institute of Cognitive Science, Osnabrück University, Osnabrueck, D-49090, Lower Saxony, Germany. · Department of Mathematics, Rhodes University, Grahamstown, Eastern Cape, 6140, Eastern Cape, South Africa. +1

  29. Orientation-Aware Unsupervised Domain Adaptation for Brain Tumor Classification Across Multi-Modal MRI

    May 5, 2026Sapna Sachan, Amulya Kumar Mahto, Prashant Wagambar PatilUnsupervised Domain AdaptationMedical Image Classification

    Indian Institute of Technology, Guwahati

  30. TumorXAI: Self-Supervised Deep Learning Framework for Explainable Brain MRI Tumor Classification

    May 3, 2026Abrar Hossain Zahin, Amit Kumar Saha, Tanvir Mridha +5Self-Supervised LearningMedical Image Classification

    Department of Computer Science and Engineering, East West University, Dhaka, 1212, Bangladesh.