Name
Abstract | ||
|---|---|---|
Accumulating evidence has shown that iron is involved in the mechanism
underlying many neurodegenerative diseases, such as Alzheimer's disease,
Parkinson's disease and Huntington's disease. Abnormal (higher) iron
accumulation has been detected in the brains of most neurodegenerative
patients, especially in the basal ganglia region. Presence of iron leads to
changes in MR signal in both magnitude and phase. Accordingly, tissues with
high iron concentration appear hypo-intense (darker than usual) in MR
contrasts. In this report, we proposed an improved binary hypointensity
description and a novel nonbinary hypointensity description based on principle
components analysis. Moreover, Kendall's rank correlation coefficient was used
to compare the complementary and redundant information provided by the two
methods in order to better understand the individual descriptions of iron
accumulation in the brain. |
Year | Venue | Keywords |
|---|---|---|
2011 | Clinical Orthopaedics and Related Research | iron,pattern recognition,rank correlation,principle component analysis |
Field | DocType | Volume |
Rank correlation,Pattern recognition,Computer science,Human brain,Artificial intelligence,Basal ganglia,Binary number | Journal | abs/1101.0 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaojing Chen | 1 | 34 | 8.09 |
| Michael S. Lew | 2 | 2742 | 166.02 |