A comprehensive survey analysis for present solutions of medical image fusion and future directions

OS Faragallah, H El-Hoseny, W El-Shafai… - IEEE …, 2020 - ieeexplore.ieee.org
The track of medical imaging has witnessed several advancements in the last years. Several
medical imaging modalities have appeared in the last decades including X-ray, Computed …

EMFusion: An unsupervised enhanced medical image fusion network

H Xu, J Ma - Information Fusion, 2021 - Elsevier
Existing image fusion methods always use the same representations for different modal
medical images. Otherwise, they solve the fusion problem by subjectively defining …

Gesenet: A general semantic-guided network with couple mask ensemble for medical image fusion

J Li, J Liu, S Zhou, Q Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
At present, multimodal medical image fusion technology has become an essential means for
researchers and doctors to predict diseases and study pathology. Nevertheless, how to …

A deep probabilistic sensing and learning model for brain tumor classification with fusion-net and HFCMIK segmentation

MVS Ramprasad, MZU Rahman… - IEEE Open Journal of …, 2022 - ieeexplore.ieee.org
Goal: Implementation of an artificial intelli gence-based medical diagnosis tool for brain
tumor classification, which is called the BTFSC-Net. Methods: Medical images are …

Medical image fusion via discrete stationary wavelet transform and an enhanced radial basis function neural network

Z Chao, X Duan, S Jia, X Guo, H Liu, F Jia - Applied Soft Computing, 2022 - Elsevier
Medical image fusion of images obtained via different modes can expand the inherent
information of original images, whereby the fused image has a superior ability to display …

Transformer-based end-to-end anatomical and functional image fusion

J Zhang, A Liu, D Wang, Y Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Medical image fusion aims to derive complementary information from medical images with
different modalities and is becoming increasingly important in clinical applications. The …

A feature extraction using probabilistic neural network and BTFSC-net model with deep learning for brain tumor classification

AS Yadav, S Kumar, GR Karetla, JC Cotrina-Aliaga… - Journal of …, 2022 - mdpi.com
Background and Objectives: Brain Tumor Fusion-based Segments and Classification-Non-
enhancing tumor (BTFSC-Net) is a hybrid system for classifying brain tumors that combine …

[PDF][PDF] Quantum Deep Learning: A Review

M Yousif, B Al-Khateeb - Iraqi Journal of Science, 2024 - iasj.net
Quantum computing is described as a process by which a system calculates output.
Quantum physics usually refers to the smallest discrete unit of any property; the basic unit of …

Saliency-guided nonsubsampled shearlet transform for multisource remote sensing image fusion

L Li, H Ma - Sensors, 2021 - mdpi.com
The rapid development of remote sensing and space technology provides multisource
remote sensing image data for earth observation in the same area. Information provided by …

Medical Image Fusion Based on Anisotropic Diffusion and Non-Subsampled Contourlet Transform.

B Goyal, A Dogra, R Khoond… - Computers …, 2023 - search.ebscohost.com
The synthesis of visual information from multiple medical imaging inputs to a single fused
image without any loss of detail and distortion is known as multimodal medical image fusion …