mlsanityData to 7 Oct 2026

Context-Gated Cross-Modal Perception with Visual Mamba for PET-CT Lung Tumor Segmentation

arXiv 2510.27508 ↗First posted 31 Oct 2025cs.CV cs.AIcited by 3

On the map: State-space sequence models (S4, Mamba) → Mamba for medical image analysis

Abstract (arXiv)

Accurate lung tumor segmentation is vital for improving diagnosis and treatment planning, and effectively combining anatomical and functional information from PET and CT remains a major challenge. In this study, we propose vMambaX, a lightweight multimodal framework integrating PET and CT scan images through a Context-Gated Cross-Modal Perception Module (CGM). Built on the Visual Mamba architecture, vMambaX adaptively enhances inter-modality feature interaction, emphasizing informative regions while suppressing noise. Evaluated on the PCLT20K dataset, the model outperforms baseline models while maintaining lower computational complexity. These results highlight the effectiveness of adaptive cross-modal gating for multimodal tumor segmentation and demonstrate the potential of vMambaX as an efficient and scalable framework for advanced lung cancer analysis. The code is available at https://github.com/arco-group/vMambaX.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Mamba for medical image analysis, one of 10 directions in State-space sequence models (S4, Mamba). Builds on 8 of its 13 references that are in the map. First posted on arXiv 31 Oct 2025.

Builds on

8 of 13 references.

Closest ancestors · 1

Same direction, newest first

  1. 2025Cross-Modal Interactive Perception Network with Mamba for Lung Tumor Segmentation in PET-CT Images21 Mar

Other references · 7

  1. 2022Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Imagescited by 823
  2. 20183D MRI brain tumor segmentation using autoencoder regularizationcited by 324
  3. 2022Medical Image Segmentation Review: The success of U-Netcited by 190
  4. 2023MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentationcited by 161
  5. 2024Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentationcited by 71
  6. 2022RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapycited by 10
  7. 2025Can Foundation Models Really Segment Tumors? A Benchmarking Odyssey in Lung CT Imagingcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026Probabilistic NDVI Forecasting from Sparse Satellite Time Series and Weather Covariatescited by 3
  2. 2026Hybrid Quantum Neural Network for Multivariate Clinical Time Series Forecastingcited by 1
  3. 2026Longitudinal NSCLC Treatment Progression via Multimodal Generative Modelscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Multimodal Slice Interaction Network Enhanced by Transfer Learning for Precise Segmentation of Internal Gross Tumor Volume in Lung Cancer PET/CT Imaging
  2. 2025Mamba Based Feature Extraction And Adaptive Multilevel Feature Fusion For 3D Tumor Segmentation From Multi-modal Medical Image
  3. 2025HybridMamba: A Dual-domain Mamba for 3D Medical Image Segmentation
  4. 2025MambaCAFU: Hybrid Multi-Scale and Multi-Attention Model with Mamba-Based Fusion for Medical Image Segmentation
  5. 2024A Multimodal Feature Distillation with Mamba-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities
  6. 2025UAM: A Unified Attention-Mamba Backbone of Multimodal Framework for Tumor Cell Classification
  7. 2024Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation
  8. 2026An approach with Visual and Tabular Mamba to multimodal medical data using Mixed Fusion