scholarly journals Enhancing Security in Medical Image Informatics using Geometrical Attacks

2019 ◽  
Vol 117 (3) ◽  
pp. 412 ◽  
Author(s):  
A. Umamageswari ◽  
M. A. Leo Vijilious
Keyword(s):  
Medical Image ◽  
Image Informatics ◽  
Geometrical Attacks

scholarly journals Medical Image Informatics for Personalized Medicine

2013 ◽  
Vol 6 (3) ◽  
pp. 30-33
Author(s):  
Anant Madabhushi ◽  
Satish Viswanath ◽  
George Lee ◽  
Pallavi Tiwari
Keyword(s):  
Personalized Medicine ◽  
Medical Image ◽  
Image Informatics

Medical image informatics infrastructure design and applications

1997 ◽  
Vol 22 (4) ◽  
pp. 279-289 ◽  
Author(s):  
H. K. Huang ◽  
S. T. C. Wong ◽  
E. Pietka
Keyword(s):  
Medical Image ◽  
Infrastructure Design ◽  
Informatics Infrastructure ◽  
Image Informatics

DWT-DFT and Logistic Map Based Watermarking Algorithm for Medical Image

2013 ◽  
Vol 380-384 ◽  
pp. 4124-4127
Author(s):  
Yao Li Liu ◽  
Jing Bing Li
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Personal Information ◽  
Logistic Map ◽  
The Internet ◽  
Visual Feature ◽  
Robust Watermarking ◽  
Feature Vectors ◽  
Strong Robustness ◽  
Geometrical Attacks

When medical image transmitted and stored on the Internet, it is vulnerable to many kinds of attacks, thus, the security of the patients personal information is low. A robust watermarking algorithm has been proposed to increase the security of medical images. The scheme obtains the visual feature vectors of the medical image using DWT-DFT. At the same time, applying Logistic Map to encrypt the watermarking image, which can enhance its security. The experiment results show that the scheme has strong robustness against geometrical attacks.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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