Image analysis using separable two-dimensional discrete orthogonal moments

2011 ◽  
Author(s):  
Hongqing Zhu
Keyword(s):  
Image Analysis ◽  
Two Dimensional ◽  
Orthogonal Moments ◽  
Discrete Orthogonal

3D image analysis by separable discrete orthogonal moments based on Krawtchouk and Tchebichef polynomials

2017 ◽  
Vol 71 ◽  
pp. 264-277 ◽  
Author(s):  
Imad Batioua ◽  
Rachid Benouini ◽  
Khalid Zenkouar ◽  
Azeddine Zahi ◽  
El Fadili Hakim
Keyword(s):  
Image Analysis ◽  
3D Image ◽  
Orthogonal Moments ◽  
3D Image Analysis ◽  
Discrete Orthogonal

scholarly journals 2D and 3D Medical Image Analysis by Discrete Orthogonal Moments

2019 ◽  
Vol 148 ◽  
pp. 428-437 ◽  
Author(s):  
O. El ogri ◽  
A. Daoui ◽  
M. Yamni ◽  
H. Karmouni ◽  
M. Sayyouri ◽  
...  
Keyword(s):  
Image Analysis ◽  
Medical Image ◽  
Medical Image Analysis ◽  
Orthogonal Moments ◽  
Discrete Orthogonal ◽  
2D And 3D

Cancer Cell Image Analysis and Visualization

2012 ◽  
pp. 233-243
Author(s):  
Tae-Yun Kim ◽  
Hae-Gil Hwang ◽  
Heung-Kook Choi
Keyword(s):  
Image Analysis ◽  
Feature Extraction ◽  
Case Studies ◽  
Cancer Cell ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Dimensional Image ◽  
The Past ◽  
Cell Image ◽  
Cell Image Analysis

We review computerized cancer cell image analysis and visualization research over the past 30 years. Image acquisition, feature extraction, classification, and visualization from two-dimensional to three-dimensional image algorithms are introduced with case studies of bladder, prostate, breast, and renal carcinomas.

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