Cover Image

Diffusion-Based Feature Denoising and Using NNMF for Robust Brain Tumor Classification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Al-kharsan, Hiba Adil, Rajkó, Róbert
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Diffusion-Based Feature Denoising with NNMF for Robust handwritten digit multi-class classification
by: Al-kharsan, Hiba Adil, et al.
Published: (2026)

Brain Tumor Classification from MRI Scans via Transfer Learning and Enhanced Feature Representation
by: Emran, Ahta-Shamul Hoque, et al.
Published: (2025)

Enhancing Brain Tumor Classification Using Vision Transformers with Colormap-Based Feature Representation on BRISC2025 Dataset
by: Ahmed, Faisal
Published: (2026)

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification
by: Ullah, Zahid, et al.
Published: (2025)

Squeezed-Eff-Net: Edge-Computed Boost of Tomography Based Brain Tumor Classification leveraging Hybrid Neural Network Architecture
by: Chowdhury, Md. Srabon, et al.
Published: (2025)

Feature Denoising Diffusion Model for Blind Image Quality Assessment
by: Li, Xudong, et al.
Published: (2024)

FedBrain-Distill: Communication-Efficient Federated Brain Tumor Classification Using Ensemble Knowledge Distillation on Non-IID Data
by: Gohari, Rasoul Jafari, et al.
Published: (2024)

D-Cube: Exploiting Hyper-Features of Diffusion Model for Robust Medical Classification
by: Jang, Minhee, et al.
Published: (2024)

Hybrid Ensemble Approaches: Optimal Deep Feature Fusion and Hyperparameter-Tuned Classifier Ensembling for Enhanced Brain Tumor Classification
by: Ullah, Zahid, et al.
Published: (2025)

Denoise to Track: Harnessing Video Diffusion Priors for Robust Correspondence
by: Yuan, Tianyu, et al.
Published: (2025)

qMRI Diffuser: Quantitative T1 Mapping of the Brain using a Denoising Diffusion Probabilistic Model
by: Wang, Shishuai, et al.
Published: (2024)

NNDM: NN_UNet Diffusion Model for Brain Tumor Segmentation
by: Makanaboyina, Sashank
Published: (2025)

Fusion-Based Brain Tumor Classification Using Deep Learning and Explainable AI, and Rule-Based Reasoning
by: Filvantorkaman, Melika, et al.
Published: (2025)

Efficient Feature Extraction and Classification Architecture for MRI-Based Brain Tumor Detection and Localization
by: Paul, Plabon, et al.
Published: (2024)

Optimized Weighted Voting System for Brain Tumor Classification Using MRI Images
by: Vu, Ha Anh
Published: (2026)

Assessment of Using Synthetic Data in Brain Tumor Segmentation
by: Jahagirdar, Aditi, et al.
Published: (2025)

Generative Adversarial Synthesis and Deep Feature Discrimination of Brain Tumor MRI Images
by: Ali, Md Sumon, et al.
Published: (2025)

DRBD-Mamba for Robust and Efficient Brain Tumor Segmentation with Analytical Insights
by: Ali, Danish, et al.
Published: (2025)

3D Vessel Graph Generation Using Denoising Diffusion
by: Prabhakar, Chinmay, et al.
Published: (2024)

VGDM: Vision-Guided Diffusion Model for Brain Tumor Detection and Segmentation
by: Behnam, Arman
Published: (2025)

Denoising Diffusion Models for Inpainting of Healthy Brain Tissue
by: Durrer, Alicia, et al.
Published: (2024)

Deep Fusion Model for Brain Tumor Classification Using Fine-Grained Gradient Preservation
by: Islam, Niful, et al.
Published: (2024)

Certified Robustness to Clean-Label Poisoning Using Diffusion Denoising
by: Hong, Sanghyun, et al.
Published: (2024)

End4: End-to-end Denoising Diffusion for Diffusion-Based Inpainting Detection
by: Wang, Fei, et al.
Published: (2025)

Robust Brain Tumor Segmentation with Incomplete MRI Modalities Using Hölder Divergence and Mutual Information-Enhanced Knowledge Transfer
by: Cheng, Runze, et al.
Published: (2025)

Automated Deception Detection from Videos: Using End-to-End Learning Based High-Level Features and Classification Approaches
by: Dinges, Laslo, et al.
Published: (2023)

Brain Tumor Classification using Vision Transformer with Selective Cross-Attention Mechanism and Feature Calibration
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024)

BTReport: A Framework for Brain Tumor Radiology Report Generation with Clinically Relevant Features
by: Rivera, Juampablo E. Heras, et al.
Published: (2026)

PathMoE: Interpretable Multimodal Interaction Experts for Pediatric Brain Tumor Classification
by: Yu, Jian, et al.
Published: (2026)

Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images
by: Liu, Xiaoyi, et al.
Published: (2024)

Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models
by: Özdenizci, Ozan, et al.
Published: (2022)

Research on Brain Tumor Classification Method Based on Improved ResNet34 Network
by: Li, Yufeng, et al.
Published: (2025)

Application of Quantum Convolutional Neural Networks for MRI-Based Brain Tumor Detection and Classification
by: Nugraha, Sugih Pratama, et al.
Published: (2025)

Directly Denoising Diffusion Models
by: Zhang, Dan, et al.
Published: (2024)

A Hybrid CNN and ML Framework for Multi-modal Classification of Movement Disorders Using MRI and Brain Structural Features
by: Li, Mengyu, et al.
Published: (2026)

Decoupling Feature Representations of Ego and Other Modalities for Incomplete Multi-modal Brain Tumor Segmentation
by: Yang, Kaixiang, et al.
Published: (2024)

Brain Tumor Radiogenomic Classification
by: Mohamed, Amr, et al.
Published: (2024)

Orientation-Aware Unsupervised Domain Adaptation for Brain Tumor Classification Across Multi-Modal MRI
by: Sachan, Sapna, et al.
Published: (2026)

D3Seg: Dependency-Aware Diffusion for Brain Tumor Segmentation with Missing Modalities
by: Ali, Danish, et al.
Published: (2026)

Adaptive and Iterative Point Cloud Denoising with Score-Based Diffusion Model
by: Wang, Zhaonan, et al.
Published: (2025)