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Non Sub-Sampled Contourlet with Joint Sparse Representation Based medical image fusion

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Computer Systems Science & Engineering 2023年第3期44卷 1989-2005页

作者： Kandasamy Kittusamy Latha Shanmuga Vadivu Sampath Kumar Department of Electronics and Communication Engineering Tamilnadu College of EngineeringCoimbatore641659India

medical image fusion is the synthesizing technology for fusing multi-modal medical information using mathematical procedures to generate better visual on the image content and high-quality image *** image fusion represents an indispensible role infixing major solutions for the complicated medical predicaments,while the recent research results have an enhanced affinity towards the preservation of medical image details,leaving color distortion and halo artifacts to remain *** paper proposes a novel method of fusing Computer Tomography(CT)and Magnetic Resonance Imaging(MRI)using a hybrid model of Non Sub-sampled Contourlet Transform(NSCT)and Joint Sparse Representation(JSR).This model gratifies the need for precise integration of medical images of different modalities,which is an essential requirement in the diagnosing process towards clinical activities and treating the patients *** the proposed model,the medical image is decomposed using NSCT which is an efficient shift variant decomposition transformation *** is exercised to extricate the common features of the medical image for the fusion *** performance analysis of the proposed system proves that the proposed image fusion technique for medical image fusion is more efficient,provides better results,and a high level of distinctness by integrating the advantages of complementary *** comparative analysis proves that the proposed technique exhibits better-quality than the existing medical image fusion practices.

关键词： medical image fusion computer tomography magnetic resonance imaging non sub-sampled contourlet transform(NSCT) joint sparse representation(JSR)

An Improved medical image fusion Algorithm for Anatomical and Functional medical images

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Chinese Journal of Biomedical Engineering(English Edition) 2009年第2期18卷 84-92页

作者： CHEN Mei-ling TAO Ling QIAN Zhi-yu College of Automation Engineering Nanjing University of Aeronautic ＆ Astronautic Nanjing 210016 China

In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data,but,not an appropriate fusion algorithm for anatomical and functional medical *** this paper,the traditional method of wavelet fusion is improved and a new fusion algorithm of anatomical and functional medical images,in which high-frequency and low-frequency coefficients are studied *** choosing high-frequency coefficients,the global gradient of each sub-image is calculated to realize adaptive fusion,so that the fused image can reserve the functional information;while choosing the low coefficients is based on the analysis of the neighborbood region energy,so that the fused image can reserve the anatomical image's edge and texture *** results and the quality evaluation parameters show that the improved fusion algorithm can enhance the edge and texture feature and retain the function information and anatomical information effectively.

关键词： medical image fusion wavelet transform fusion algorithm quality evaluation

Wavelet Packet-based Feedback System for medical image fusion

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Semiconductor Photonics and Technology 2010年第2期16卷 103-109页

作者： YU Oiuyan IHAN Xiaojun Department of Information and Communication Tianjin Polytechnic University Tianjin 300160 CHN

In order to meet the requirements of medical research,diagnosis and treatment,a new algorithm for image fusion based on the wavelet packet transform in conjunction with both subjective and objective assessments is put forward in the *** to the wavelet transform,the wavelet packet transform is more intricate and effective for the medical image *** indicated by the experimental results,parameters of the feedback system of the new algorithm are significantly superior to those of the wavelet transform,with practicability and accuracy.

关键词： medical image fusion wavelet packet subjective assessment feedback system

Wavelet Packet-based Feedback System for medical image fusion

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Semiconductor Photonics and Technology 2010年第Z1期 102-108页

作者： YU Qiuyan1,HAN Xiaojun2(Department of Information and Communication,Tianjin Polytechnic University,Tianjin 300160,CHN)

关键词： medical image fusion wavelet packet subjective assessment feedback system

Multimodal medical image non-rigid registration and fusion based on cubit spline,FFD and wavelet methods

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Multimodal medical image non-rigid registration and fusion b...

Brain Tumor Classification Using image fusion and EFPA-SVM Classifier

首届全国分子核医学暨分子影像学学术交流会

作者： YuanLie He, Ping Chen College of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640,China The First Affiliated Hospital of Guangzhou medical College, Guangzhou 510120, China

Object image registration is the process of aligning images so that corresponding features can easily be related. The term is also used to mean aligning images with a computer model or aligning features in an image with locations in physical space. The images might be acquired with different sensors (e.g. sensitive to different parts or the electromagnetic spectrum) or the same sensor at different times. image registration has applications in many fields, and the one that is addressed in this article is medical imaging. This encompasses a wide range of image usage, but the main emphasis is on radiological imaging medical imaging is about establishing shape, structure, size, and spatial relationships of anatomical structures within the patient, together with spatial information about function and any pathology or other abnormality. Establishing the correspondence of spatial information in medical images and equivalent structures in the body is fundamental to medical image interpretation and analysis. It is now common for patients to be imaged multiple times, either repeated imaging with a single modality, or imaging with different modalities. It is also common for patients to be imaged dynamically, that is to have sequences of images acquired, often at many frames per second. The ever-increasing amount of image data acquired makes it more and more desirable to relate one image to another to assist in extracting relevant clinical information. The PET/CT scanner can complete the PET and CT scan on the same equipment instead of moving the patient between different scanners. That decreases the movement of the patient and increases the accuracy of the PET and CT image mergence. Generally, the PET/CT scanner merges the CT and PET images according their slice numbers directly. In fact, the slice space of the CT images and the PET images are different (about 0.48mm discrepancy), even they are coming from the most advance PET/CT scanner. It is about two hundred CT images and

关键词： Non-rigid registration medical image fusion Cubit spline interpolation Free form deformation Wavelet analysis

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Intelligent Automation & Soft Computing 2023年第3期35卷 2837-2855页

作者： P.P.Fathimathul Rajeena R.Sivakumar Anna University Chennai600025India Department of Computer Science and Engineering Tamilnadu College of EngineeringCoimbatore641659India

An accurate and early diagnosis of brain tumors based on medical ima-ging modalities is of great interest because brain tumors are a harmful threat to a person’s health *** medical imaging techniques have been used to analyze brain tumors,including computed tomography(CT)and magnetic reso-nance imaging(MRI).CT provides information about dense tissues,whereas MRI gives information about soft ***,the fusion of CT and MRI images has little effect on enhancing the accuracy of the diagnosis of brain ***,machine learning methods have been adopted to diagnose brain tumors in recent *** paper intends to develop a novel scheme to detect and classify brain tumors based on fused CT and MRI *** pro-posed approach starts with preprocessing the images to reduce the ***,fusion rules are applied to get the fused image,and a segmentation algorithm is employed to isolate the tumor region from the background to isolate the tumor ***,a machine learning classiﬁer classiﬁed the brain images into benign and malignant *** statistical measures evaluate the classi-ﬁcation potential of the proposed *** outcomes are provided,and the Enhanced Flower Pollination Algorithm(EFPA)system shows that it out-performs other brain tumor classiﬁcation methods considered for comparison.

关键词： Brain tumor classiﬁcation improved wavelet threshold integer wavelet transform medical image fusion

fusion of medical images in Wavelet Domain:A Hybrid Implementation

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Computer Modeling in Engineering & Sciences 2020年第1期122卷 303-321页

作者： Satya Prakash Yadav Sachin Yadav Department of Information Technology ABES Institute of Technology(ABESIT)GhaziabadIndia Department of Computer Science and Engineering G.L.Bajaj Institute of Technology and Management(GLBITM)Greater NoidaIndia

This paper presents a low intricate,profoundly energy effective MRI images combination intended for remote visual sensor frameworks which leads to improved understanding and implementation of treatment;especially for *** is done by combining the original picture which leads to a significant reduction in the computation time and *** proposed technique conquers the calculation and energy impediment of low power tools and is examined as far as picture quality and energy is *** are performed utilizing MATLAB 2018a,to quantify the resultant vitality investment funds and the reproduction results show that the proposed calculation is very quick and devours just around 1%of vitality decomposition by the hybrid combination ***,the effortlessness of our proposed strategy makes it increasingly suitable for continuous applications.

关键词： medical image fusion wavelet transform DWT DCT ICA fusion techniques multimodal fusion

Wavelet based Approach for Fusing Computed Tomography and Magnetic Resonance images

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Wavelet based Approach for Fusing Computed Tomography and Ma...