Discrimination between Alzheimer Disease, Mild Cognitive Impairment, and Normal Aging by Using Automated Segmentation of the Hippocampus

Abstract

This automated method can serve as an alternative to manual tracing and may thus prove useful in assisting with the diagnosis of AD.

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

“…In their method, MRI images were segmented into grey matter (GM), white matter and CSF using SPM. Colliot et al [44] developed an automated segmentation method to aid distinguish between patients with AD, mild cognitive impairment (MCI) and elderly controls. Hamou et al [45] proposed a computerised method based on cluster analysis and decision tree for analysing processing MRI image in the AD diagnosis.…”

Simultaneous segmentation and grading of anatomical structures for patient's classification: Application to Alzheimer's disease

“…Among these methods, several have been used to classify AD patients using HC volume (Chupin et al, 2009a;Colliot et al, 2008;Morra et al, 2010;Mueller et al, 2010). Despite the high segmentation accuracy of the new HC segmentation approaches, using the HC volume enables a separation between AD and cognitively normal (CN) subjects with a success rate only around 72-74% over the entire Alzheimer's Disease Neuroimaging Initiative (ADNI) database (Cuingnet et al, 2010).…”

Towards Accurate, Automatic Segmentation of the Hippocampus and Amygdala from MRI

“…Since this procedure required considerable computational effort, Aljabar et al optimized the technique by selecting the 'n' most appropriate atlases from the library using normalized mutual information [22]. Recently, Chupin et al reported on an ingenious Markovian model region growing procedure that uses morphometric and topological constraints with anatomical rules to identify HC-specific landmarks segment the HC and AG [23,24]. At present, the work of Barnes [18], Chupin [23] and Gousias [25] yield the best published segmentation results for hippocampus (see Table 1 for a methods survey).…”