Many researchers have developed Computer-Aided Diagnosis (CAD) systems that automatically diagnose Alzheimer's disease (AD) before it can be detected by cognitive tests. CAD is becoming increasingly important in medical and clinical research. CAD is used to support decisions using data from medical imaging. CAD systems analyze and evaluate radiology data in a short period of time. It helps to improve the accuracy and efficiency of radiologists in their medical diagnosis.

To show that high-performance CAD can reduce diagnostic errors, enormous research efforts have been undertaken to discover, characterize, and quantify biological markers for AD, especially during the preclinical or prodromal stages of AD so that therapeutic treatment strategies may be initiated.

The aim of this Special Issue is to bring together original research and review articles concerning recent advances and applications of CAD in the identification of biomarkers in AD. Submissions about new trends in measuring and processing biomarkers are welcome. Research on the use of intelligent algorithms to analyze biomarkers, support diagnosis, decision making, and classification is also encouraged.

Potential topics include but are not limited to the following:

• Neuroimaging markers for the diagnosis of Alzheimer's disease: neuroinflammation, AD, and Dementia
• Dementia diagnosis using Amyloid, Tau, Neurodegeneration and Vascular markers (ATN(V))
• VBM-based Alzheimer’s disease detection
• Automatic detection of Alzheimer’s disease using a computer-aided diagnosis (CAD) system
• Imaging techniques such as MRI, PET, and CT scan
• Mapping between s-MRI and PET for AD diagnosis support
• CAD development for AD detection with HC/NC and MCI
• Multimodal imaging techniques combining MRI, CSF, and PET data