Medical imaging diagnosis of early Alzheimer's disease

被引:8
作者
El-Gamal, Fatma El-Zahraa A. [1 ,2 ]
Elmogy, Mohammed M. [1 ,2 ]
Ghazal, Mohammed [2 ,3 ]
Atwan, Ahmed [1 ]
Casanova, Manuel F. [4 ]
Barnes, Gregory N. [5 ]
El-Baz, Ayman S. [2 ]
Hajjdiab, Hassan [3 ]
机构
[1] Mansoura Univ, Fac Comp & Informat, Informat Technol Dept, Mansoura 35516, Egypt
[2] Univ Louisville, BioImaging Lab, Dept Bioengn, Louisville, KY 40292 USA
[3] Abu Dhabi Univ, Dept Elect & Comp Engn, Abu Dhabi, U Arab Emirates
[4] Univ South Carolina, Sch Med, Greenville, SC 29208 USA
[5] Univ Louisville, Autism Ctr, Dept Neurol, Louisville, KY 40217 USA
来源
FRONTIERS IN BIOSCIENCE-LANDMARK | 2018年 / 23卷
关键词
Alzheimer's disease; Early Diagnosis; Medical Imaging Modalities; Clinical Findings; Computer-Based Findings; Fusion; Review; MILD COGNITIVE IMPAIRMENT; COMPUTER-AIDED DIAGNOSIS; PRINCIPAL COMPONENT ANALYSIS; PARTIAL LEAST-SQUARES; FDG-PET; FEATURE REPRESENTATION; FEATURE-SELECTION; BRAIN IMAGES; CLASSIFICATION; BIOMARKERS;
D O I
10.2741/4612
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases that influences the central nervous system, often leading to dire consequences for quality of life. The disease goes through some stages mainly divided into early, moderate, and severe. Among them, the early stage is the most important as medical intervention has the potential to alter the natural progression of the condition. In practice, the early diagnosis is a challenge since the neurodegenerative changes can precede the onset of clinical symptoms by 10-15 years. This factor along with other known and unknown ones, hinder the ability for the early diagnosis and treatment of AD. Numerous research efforts have been proposed to address the complex characteristics of AD exploiting various tests including brain imaging that is massively utilized due to its powerful features. This paper aims to highlight our present knowledge on the clinical and computer-based attempts at early diagnosis of AD. We concluded that the door is still open for further research especially with the rapid advances in scanning and computer-based technologies.
引用
收藏
页码:671 / 725
页数:55
相关论文
共 112 条
  • [21] Association rule-based feature selection method for Alzheimer's disease diagnosis
    Chaves, R.
    Ramirez, J.
    Gorriz, J. M.
    Puntonet, C. G.
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (14) : 11766 - 11774
  • [22] Chaves R, 2011, LECT NOTES ARTIF INT, V6678, P148, DOI 10.1007/978-3-642-21219-2_20
  • [23] Chaves R, 2010, LECT NOTES ARTIF INT, V6076, P452, DOI 10.1007/978-3-642-13769-3_55
  • [24] Multimodal manifold-regularized transfer learning for MCI conversion prediction
    Cheng, Bo
    Liu, Mingxia
    Suk, Heung-Il
    Shen, Dinggang
    Zhang, Daoqiang
    [J]. BRAIN IMAGING AND BEHAVIOR, 2015, 9 (04) : 913 - 926
  • [25] Mild cognitive impairment -: Can FDG-PET predict who is to rapidly convert to Alzheimer's disease?
    Chételat, G
    Desgranges, B
    de la Sayette, V
    Viader, F
    Eustache, F
    Baron, JC
    [J]. NEUROLOGY, 2003, 60 (08) : 1374 - 1377
  • [26] Amyloid imaging in cognitively normal individuals, at-risk populations and preclinical Alzheimer's disease
    Chetelat, Gael
    La Joie, Renaud
    Villain, Nicolas
    Perrotin, Audrey
    de La Sayette, Vincent
    Eustache, Francis
    Vandenberghe, Rik
    [J]. NEUROIMAGE-CLINICAL, 2013, 2 : 356 - 365
  • [27] Early detection of Alzheimer's disease using PiB and FDG PET
    Cohen, Ann D.
    Klunk, William E.
    [J]. NEUROBIOLOGY OF DISEASE, 2014, 72 : 117 - 122
  • [28] MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer's disease
    Dickerson, BC
    Goncharova, I
    Sullivan, MP
    Forchetti, C
    Wilson, RS
    Bennett, DA
    Beckett, LA
    deToledo-Morrell, L
    [J]. NEUROBIOLOGY OF AGING, 2001, 22 (05) : 747 - 754
  • [29] Drzezga A, 2005, J NUCL MED, V46, P1625
  • [30] Current trends in medical image registration and fusion
    El-Gamal, Fatma El-Zahraa Ahmed
    Elmogy, Mohammed
    Atwan, Ahmed
    [J]. EGYPTIAN INFORMATICS JOURNAL, 2016, 17 (01) : 99 - 124