Optimization Techniques for Removing Noise in Digital Medical Images

2021 ◽  
pp. 243-266
Author(s):  
D. Devasena ◽  
M. Jagadeeswari ◽  
B. Sharmila ◽  
K. Srinivasan
Author(s):  
S.N. Kumar ◽  
A. Lenin Fred ◽  
Parasuraman Padmanabhan ◽  
Balazs Gulyas ◽  
Ajay Kumar Haridhas ◽  
...  

2021 ◽  
Author(s):  
Anthony Vincent B ◽  
Cecil Donald A ◽  
B J Hubert Shanthan ◽  
Ankur Singh Bist ◽  
Haider mehraj ◽  
...  

Abstract The advent of the Internet of Things (IoT) is to transform the health care sector and lead to the development of the Internet of Health Things (IoHT). This technology exceeds existing human services mechanically, financially, and socially. This paper used an advanced cryptographic framework that includes optimization strategies to look at IoHT medical image protection. The patient data kept on a cloud server which was detected and sensed from the IoHT Healthcare devices. It's critical to ensure the safety and privacy of patient clinical images in the cloud; here, an enhanced security framework for health information promotes trust. Next, we presented health care providers who could provide the full range of medical facilities for IoHT participants. In the process of encrypting/decrypting elliptical curves, the optimal key is selected using the Grasshopper Particle Swarm Optimization (GOPSO) to increase the security standard of medical images. Medical images are protected within IoHT by using this approach.The implementation results were analyzed and compared with a variety of encryption algorithms and their optimization techniques. The effectiveness of the proposed methods and the results show that the medical image is secure and prevents attacks in IoHT-based health care systems.


Author(s):  
T. Tirupal ◽  
B. Chandra Mohan ◽  
S. Srinivas Kumar

The main objective of image fusion for multimodal medical images is to retrieve valuable information by combining multiple images obtained from various sources into a single image suitable for better diagnosis. In this paper, a detailed survey on various existing medical image fusion algorithms, with a comparative discussion is presented. Image fusion algorithms available in the current literature are categorized into various methods known as (1) morphological methods, (2) human value system operator based methods, (3) sub-band decomposition methods, (4) neural network based methods, and (5) fuzzy logic based methods. This research concludes that even though there exists a few open-ended creative and logical difficulties, the fusion of medical images in many combinations assists in utilizing medical image fusion for medicinal diagnostics and examination. There is tremendous progress in the fields of deep learning, artificial intelligence and bio-inspired optimization techniques. Effective utilization of these techniques can be used to further improve the efficiency of image fusion algorithms.


EMJ Radiology ◽  
2020 ◽  
Author(s):  
Filippo Pesapane

Radiomics is a science that investigates a large number of features from medical images using data-characterisation algorithms, with the aim to analyse disease characteristics that are indistinguishable to the naked eye. Radiogenomics attempts to establish and examine the relationship between tumour genomic characteristics and their radiologic appearance. Although there is certainly a lot to learn from these relationships, one could ask the question: what is the practical significance of radiogenomic discoveries? This increasing interest in such applications inevitably raises numerous legal and ethical questions. In an environment such as the technology field, which changes quickly and unpredictably, regulations need to be timely in order to be relevant.  In this paper, issues that must be solved to make the future applications of this innovative technology safe and useful are analysed.


2020 ◽  
Vol 14 (4) ◽  
pp. 7446-7468
Author(s):  
Manish Sharma ◽  
Beena D. Baloni

In a turbofan engine, the air is brought from the low to the high-pressure compressor through an intermediate compressor duct. Weight and design space limitations impel to its design as an S-shaped. Despite it, the intermediate duct has to guide the flow carefully to the high-pressure compressor without disturbances and flow separations hence, flow analysis within the duct has been attractive to the researchers ever since its inception. Consequently, a number of researchers and experimentalists from the aerospace industry could not keep themselves away from this research. Further demand for increasing by-pass ratio will change the shape and weight of the duct that uplift encourages them to continue research in this field. Innumerable studies related to S-shaped duct have proven that its performance depends on many factors like curvature, upstream compressor’s vortices, swirl, insertion of struts, geometrical aspects, Mach number and many more. The application of flow control devices, wall shape optimization techniques, and integrated concepts lead a better system performance and shorten the duct length.  This review paper is an endeavor to encapsulate all the above aspects and finally, it can be concluded that the intermediate duct is a key component to keep the overall weight and specific fuel consumption low. The shape and curvature of the duct significantly affect the pressure distortion. The wall static pressure distribution along the inner wall significantly higher than that of the outer wall. Duct pressure loss enhances with the aggressive design of duct, incursion of struts, thick inlet boundary layer and higher swirl at the inlet. Thus, one should focus on research areas for better aerodynamic effects of the above parameters which give duct design with optimum pressure loss and non-uniformity within the duct.


2011 ◽  
Vol 39 (4) ◽  
pp. 223-244 ◽  
Author(s):  
Y. Nakajima

Abstract The tire technology related with the computational mechanics is reviewed from the standpoint of yesterday, today, and tomorrow. Yesterday: A finite element method was developed in the 1950s as a tool of computational mechanics. In the tire manufacturers, finite element analysis (FEA) was started applying to a tire analysis in the beginning of 1970s and this was much earlier than the vehicle industry, electric industry, and others. The main reason was that construction and configurations of a tire were so complicated that analytical approach could not solve many problems related with tire mechanics. Since commercial software was not so popular in 1970s, in-house axisymmetric codes were developed for three kinds of application such as stress/strain, heat conduction, and modal analysis. Since FEA could make the stress/strain visible in a tire, the application area was mainly tire durability. Today: combining FEA with optimization techniques, the tire design procedure is drastically changed in side wall shape, tire crown shape, pitch variation, tire pattern, etc. So the computational mechanics becomes an indispensable tool for tire industry. Furthermore, an insight to improve tire performance is obtained from the optimized solution and the new technologies were created from the insight. Then, FEA is applied to various areas such as hydroplaning and snow traction based on the formulation of fluid–tire interaction. Since the computational mechanics enables us to see what we could not see, new tire patterns were developed by seeing the streamline in tire contact area and shear stress in snow in traction.Tomorrow: The computational mechanics will be applied in multidisciplinary areas and nano-scale areas to create new technologies. The environmental subjects will be more important such as rolling resistance, noise and wear.


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