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Multimodal classification of Alzheimer's disease and mild cognitive impairment
TLDR
We propose to combine three modalities of biomarkers, i.e., MRI, FDG-PET, and CSF, to discriminate between AD (or MCI) and healthy controls, using a kernel combination method. Expand
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Deep convolutional neural networks for multi-modality isointense infant brain image segmentation
TLDR
The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. Expand
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Enriched white matter connectivity networks for accurate identification of MCI patients
TLDR
We propose an effective network-based multivariate classification algorithm, using a collection of measures derived from white matter (WM) connectivity networks, to accurately identify MCI patients from normal controls. Expand
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Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
TLDR
We propose a novel method for a high-level latent and shared feature representation from neuroimaging modalities via deep learning. Expand
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Medical Image Synthesis with Context-Aware Generative Adversarial Networks
TLDR
We train a fully convolutional network (FCN) to generate CT images from MR images, and also outperforms three state-of-the-art methods under comparison. Expand
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Identification of MCI individuals using structural and functional connectivity networks
TLDR
This study focuses on integrating multiple imaging modalities to identify individuals at risk for mild cognitive impairment (MCI). Expand
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Latent feature representation with stacked auto-encoder for AD/MCI diagnosis
Recently, there have been great interests for computer-aided diagnosis of Alzheimer’s disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods thatExpand
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Lung Infection Quantification of COVID-19 in CT Images with Deep Learning
TLDR
A deep learning (DL)-based segmentation system is developed to automatically quantify infection regions of interest (ROIs) and their volumetric ratios. Expand
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Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19
  • F. Shi, J. Wang, +6 authors D. Shen
  • Computer Science, Medicine
  • IEEE reviews in biomedical engineering
  • 6 April 2020
TLDR
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world. Expand
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Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients
TLDR
In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. Expand
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