Perceptual linearization of video-display monitors for medical image presentation

1994 ◽  
Author(s):  
Bradley M. Hemminger ◽  
Richard E. Johnston ◽  
Jannick P. Rolland ◽  
Keith E. Muller
Keyword(s):  
Medical Image ◽  
Video Display ◽  
Image Presentation ◽  
Perceptual Linearization

scholarly journals Introduction to perceptual linearization of video display systems for medical image presentation

1995 ◽  
Vol 8 (1) ◽  
pp. 21-34 ◽  
Author(s):  
Bradley M. Hemminger ◽  
R. Eugene Johnston ◽  
Jannick P. Rolland ◽  
Keith E. Muller
Keyword(s):  
Medical Image ◽  
Video Display ◽  
Image Presentation ◽  
Display Systems ◽  
Perceptual Linearization

scholarly journals A Comparison of WebRTC and Conventional Videoconferencing for Synchronized Remote Medical Image Presentation

2021 ◽  
Author(s):  
Vishal Patel ◽  
Charles H. Li ◽  
Van Rye ◽  
Chia-Shang J. Liu ◽  
Alexander Lerner ◽  
...  
Keyword(s):  
Medical Image ◽  
Image Presentation

Stress as a function of the rate at which information is presented on a video display terminal

1983 ◽  
Author(s):  
Woodrow Barfield ◽  
Bill West ◽  
Mica Robertson ◽  
F. Lynne Taylor ◽  
Nelson Tamplin
Keyword(s):  
Video Display ◽  
Video Display Terminal

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.

Sign in / Sign up

Export Citation Format

Share Document