Brain Tumor Classification

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (52 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging
  13 Apr 2023 2 repositories listed
  Recent applications of deep convolutional neural networks in medical imaging raise concerns about their interpretability.
• Deep Multimodal Guidance for Medical Image Classification
  10 Mar 2022 2 repositories listed
  Furthermore, in the case of brain tumor classification, our method outperforms the model trained on the superior modality while producing comparable results to the model that uses both modalities during inference.
• HMM Model for Brain Tumor Detection and Classification
  22 Jun 2021 2 repositories listed
  Brain tumor is one of the significant problems that has taken the life of a lot of people in recent times.
• MediAug: Exploring Visual Augmentation in Medical Imaging
  26 Apr 2025 1 repository listed
  Data augmentation is essential in medical imaging for improving classification accuracy, lesion detection, and organ segmentation under limited data conditions.
• Edge-Enhanced Dilated Residual Attention Network for Multimodal Medical Image Fusion
  18 Nov 2024 1 repository listed
  Multimodal medical image fusion is a crucial task that combines complementary information from different imaging modalities into a unified representation, thereby enhancing diagnostic accuracy and treatment planning.
• Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decomposition
  3 Oct 2024 1 repository listed
  The promising results show that the integration of TDA, ML, and low-rank approximation methods is a successful approach for brain tumor identification and categorization, providing a solid foundation for further study…
• FedBrain-Distill: Communication-Efficient Federated Brain Tumor Classification Using Ensemble Knowledge Distillation on Non-IID Data
  9 Sep 2024 1 repository listed
  In this paper, we propose FedBrain-Distill, an approach that leverages Knowledge Distillation (KD) in an FL setting that maintains the users privacy and ensures the independence of FL clients in terms of model…
• MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor Classification
  13 Apr 2024 1 repository listed
  Specifically, we introduce a concise multi-scale module to merge attentive features from quadruplet attention layers, and produces attribution maps.
• Optimizing Brain Tumor Classification: A Comprehensive Study on Transfer Learning and Imbalance Handling in Deep Learning Models
  13 Aug 2023 1 repository listed
  By leveraging a publicly available Brain MRI dataset, the experiment evaluated various transfer learning models for classifying different tumor types, including meningioma, glioma, and pituitary tumors.
• Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing Tasks
  26 Jun 2023 1 repository listed
  Feature-Imitating-Networks (FINs) are neural networks that are first trained to approximate closed-form statistical features (e.
• LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
  20 Jun 2023 1 repository listed Syntology ran 4 of 13 samples · 9 unverified · 13 pointer-only (licence)
  While pre-trained deep networks on ImageNet and vision-language foundation models trained on web-scale data are prevailing approaches, their effectiveness on medical tasks is limited due to the significant domain shift…

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.