Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer’s Disease Diagnosis
By Manhua Liu, Danni Cheng, Kundong Wang, Yaping Wang. 2018
374 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Neurology
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Citations in the corpus
- An overview of deep learning in medical imaging focusing on MRI (2018, methodology): “Tested on 105 subjects from the Human Connectome Project Brain age [273] Chronological age prediction from raw brain T1-MRI data, also testing the heritability of brain-predicted age using a sample of 62 monozygotic and dizygotic twins Alzheimer’s disease [274] Landmark-based deep multi-instance lea”
- A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease (2019, neutral): “…the MRI data for identifying biomarkers and deciphering the disease etiology (Cao et al., 2018; Cao et al., 2017; Cheng and Wang, 2017; Hosseini-Asl et al., 2016; Jr et al., 2011; Liu et al., 2018a; Liu et al., 2018b; Ortiz et al., 2016; Suk et al., 2015; Zhang et al., 2016; Zhang et al., 2017).”