Article

Selective State-Space Models in Medical Image Processing

2026-04-14

Abstract excerpt

In medical image analysis, modeling local and global features in high-resolution data presents a significant challenge. While the widely used Convolutional Neural Networks (CNNs) struggle to capture long-range dependencies between distant pixels, the high computational cost (O(N2)) of Vision Transformer (ViT) architectures causes bottlenecks in clinical applications. This study investigates the integration of Mamb...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 5b6a55f3-bd50-537f-95a3-9fa711e2922c
DOI: 10.20944/preprints202604.0948.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Selective State-Space Models in Medical Image ProcessingDOI 10.20944/preprints202604.0948.v1Read

Selective State Space Models in Medical Imaging: A Systematic Review of Mamba-Based Architectures and Clinical ApplicationsSemantic proximity Read

Advances in Deep Learning for Medical Imaging: Foundations, Evolution, and ImpactSemantic proximity Read

CLSENet: A Continuous Learning Semantic Enhancement Network for Medical Image PerceptionSemantic proximity Read

A Unified Vision Transformer and Convolutional Neural Network Framework for Multi-Domain Cancer ClassificationSemantic proximity Read

A Novel Approach for Integrating Mamba and Diffusion in 3D Medical ImagingSemantic proximity Read

Next-Gen ST-CNN: A Lightweight Spatiotemporal Deep Learning Model for Accurate and Fast Brain Tumor DetectionSemantic proximity Read

Do Hybrid CNN–Transformer Architectures Really Generalize? A Systematic Review for Medical ImagingSemantic proximity Read

Semantically-Guided State-Space Models for Data-Efficient and Robust Cross-Platform Virtual StainingSemantic proximity Read

Explainable Hybrid ConvNeXt–Vision Transformer Model for Pneumonia Detection from Chest X-ray ImagesSemantic proximity Read

Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View MammogramsSemantic proximity Read

A survey on attention mechanisms for medical applications: are we moving towards better algorithms?Semantic proximity Read

The U-shaped Transformer architecture for precise retinal vessel segmentationSemantic proximity Read