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A spatial squeeze and multimodal feature fusion attention network for multiple tumor segmentation from PET–CT Volumes

  • Published:2023-05 Issue: Volume:121 Page:105955
  • ISSN:0952-1976
  • Container-title:Engineering Applications of Artificial Intelligence
  • language:en
  • Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Diao Zhaoshuo,Jiang Huiyan,Shi Tianyu

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference29 articles.

1. Recurrent feature fusion learning for multi-modality pet-ct tumor segmentation;Bi;Comput. Methods Programs Biomed.,2021

2. Multi-stage thresholded region classification for whole-body PET-CT lymphoma studies;Bi,2014

3. PET/CT: Form and function;Blodgett;Radiology,2007

4. GCNet: Non-local networks meet squeeze-excitation networks and beyond;Cao,2019

5. Robust multimodal brain tumor segmentation via feature disentanglement and gated fusion;Chen,2019

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3. Bilateral Cross-Modal Fusion Network for Multimodal Whole-Body Tumor Segmentation;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27

4. Multi-modal tumor segmentation methods based on deep learning: a narrative review;Quantitative Imaging in Medicine and Surgery;2024-01

5. 3D PET/CT Tumor Co-Segmentation Based on Background Subtraction Hybrid Active Contour Model;International Journal of Pattern Recognition and Artificial Intelligence;2023-06-30
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