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Novel medical image cryptogram technology based on segmentation and DNA encoding
This paper proposes a novel medical image cryptogram technology based on a fast and robust fuzzy C-means clustering image segmentation method and...
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Comprehensive performance analysis of different medical image fusion techniques for accurate healthcare diagnosis applications
The advancement of medical imaging has led to the acquisition of image data from multiple modalities, necessitating the development of robust...
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Medical image fusion based on transfer learning techniques and coupled neural P systems
Medical image fusion is an essential task for clinical diagnosis because it allows physicians to make more accurate diagnoses. Up to now, many...
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Possibilistic picture fuzzy product partition C-means clustering incorporating rich local information for medical image segmentation
Picture fuzzy C-means clustering is a new computational intelligence method that has more significant potential advantages than fuzzy clustering in...
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A hybrid approach of simultaneous segmentation and classification for medical image analysis
Medical image analysis is a crucial step required for accurate disease diagnosis, treatment planning, and condition monitoring. In recent years, the...
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An approach for medical image registration using a Double Exponential-Dynamic Group Based Cooperative Optimization algorithm
Medical image registration is the process of aligning multiple medical images, volumes, or surfaces to a common coordinate system . In multiple...
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Batch medical image encryption using 3D Latin cube-based simultaneous permutation and diffusion
Nowadays, numerous encryption schemes have been proposed in response to the growing concerns regarding the security of individuals’ health...
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Gaussian quantum arithmetic optimization-based histogram equalization for medical image enhancement
The quality of medical images is critical for accurate diagnosis. This paper introduces a novel Quantum-behaved Arithmetic Optimization Algorithm...
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A novel CNN Architecture with an efficient Channelization for Histopathological Medical Image Classification
Diagnosing the issues in the tissues has always been a challenging task on medical images like MRI, Mammogram, Computed Tomography, X-Ray, Retinal...
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Pullikolam assisted medical image watermarking on reconfigurable hardware
This paper proposes that Pullikolam influenced medical image watermarking on Field Programmable Gate Array (FPGA). This watermarking scheme undergoes...
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RKSeg+: make full use of Runge–Kutta methods in medical image segmentation
The dynamical system perspective has been used to build efficient image classification networks and semantic segmentation networks. Furthermore, the...
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AutoEncoder-Driven Multimodal Collaborative Learning for Medical Image Synthesis
Multimodal medical images have been widely applied in various clinical diagnoses and treatments. Due to the practical restrictions, certain...
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Medical image fusion based on type-2 fuzzy sets with teaching learning based optimization
The main objective of image fusion for multimodal medical images is to retrieve valuable information by combining multiple images obtained from...
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A Complete Review on Image Denoising Techniques for Medical Images
Medical imaging methods, such as CT scans, MRI scans, X-rays, and ultrasound imaging, are widely used for diagnosis in the healthcare domain....
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An Operative Medical Angio-Image Improvement with Adaptive Fractional Differential Filter
The quantitative changes in the structure of the blood vessels are indications of an altered physiological or compulsive situation, and they are...
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Dense deep transformer for medical image segmentation: DDTraMIS
In this work, DDTraMIS architecture based on vision has been designed for medical image segmentation for different medical imaging such as MRI and...
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Multi-modal medical image fusion in NSST domain for internet of medical things
The Internet of Medical Things (IoMT) has included a new layer for development and smart infrastructure growth in the medical field. Besides, the...
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A novel steganographic technique for medical image using SVM and IWT
This study presents an efficient authentication scheme for digital image steganography on medical images benefiting from the combination of both...
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G-UNeXt: a lightweight MLP-based network for reducing semantic gap in medical image segmentation
In recent years, medical image segmentation methods based on deep learning have been of great importance for disease diagnosis and treatment planning...
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SS-SSAN: a self-supervised subspace attentional network for multi-modal medical image fusion
Multi-modal medical image fusion (MMIF) is used to merge multiple modes of medical images for better imaging quality and more comprehensive...
