Self-adjusting binary search trees: an investigation of their space and time efficiency in texture analysis of magnetic resonance images using the spatial gray-level dependence method

1998 ◽  
Author(s):  
Andreas I. Svolos ◽  
Andrew Todd-Pokropek
Keyword(s):  
Magnetic Resonance ◽  
Texture Analysis ◽  
Magnetic Resonance Images ◽  
Binary Search ◽  
Gray Level ◽  
Binary Search Trees ◽  
Search Trees ◽  
Time Efficiency ◽  
Space And Time

scholarly journals ALTEA: A Software Tool for the Evaluation of New Biomarkers for Alzheimer’s Disease by Means of Textures Analysis on Magnetic Resonance Images

Diagnostics ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 47 ◽  
Author(s):  
Carlos López-Gómez ◽  
Rafael Ortiz-Ramón ◽  
Enrique Mollá-Olmos ◽  
David Moratal ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Texture Analysis ◽  
Software Tool ◽  
Magnetic Resonance Images ◽  
Gray Level ◽  
Predictive Capacity ◽  
Texture Parameters ◽  
New Biomarkers

The current criteria for diagnosing Alzheimer’s disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has become one of the main research focuses. The purpose of the present study was to evaluate a set of texture parameters as potential biomarkers of the disease. To this end, the ALTEA (ALzheimer TExture Analyzer) software tool was created to perform 2D and 3D texture analysis on magnetic resonance images. This intuitive tool was used to analyze textures of circular and spherical regions situated in the right and left hippocampi of a cohort of 105 patients: 35 AD patients, 35 patients with early mild cognitive impairment (EMCI) and 35 cognitively normal (CN) subjects. A total of 25 statistical texture parameters derived from the histogram, the Gray-Level Co-occurrence Matrix and the Gray-Level Run-Length Matrix, were extracted from each region and analyzed statistically to study their predictive capacity. Several textural parameters were statistically significant (p < 0.05) when differentiating AD subjects from CN and EMCI patients, which indicates that texture analysis could help to identify the presence of AD.

scholarly journals Adaptive structuring of binary search trees using conditional rotations

1993 ◽  
Vol 5 (4) ◽  
pp. 695-704 ◽  
Author(s):  
R.P. Cheetham ◽  
B.J. Oommen ◽  
D.T.H. Ng
Keyword(s):  
Binary Search ◽  
Binary Search Trees ◽  
Search Trees
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