Previous brain morphology-related diagnostic models for attention-deficit hyperactivity disorder (ADHD) were based on regional features. However, building a model of individual interregional morphological connectivity is a challenging task. This stud...
International journal of computer assisted radiology and surgery
Jul 19, 2018
PURPOSE: We present a cross-modality and fully automatic pipeline for labeling of intervertebral discs and vertebrae in volumetric data of the lumbar and thoracolumbar spine. The main goal is to provide an algorithm that is applicable to a wide range...
Recent neuroimaging studies identified posterior regions in the temporal and parietal lobes as neuro-functional correlates of subitizing and global Gestalt perception. Beyond notable overlap on a neuronal level both mechanisms are remarkably similar ...
Attention Deficit Hyperactive Disorder (ADHD) is one of the most common diseases in school aged children. In this paper, we consider using fMRI data with classification techniques to aid the diagnosis of ADHD and propose a bi-objective ADHD classific...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jul 16, 2018
Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown to be a sensitive and reliable metric for studying pathological brain mechanisms across various chronic pain patient populations. However, the relati...
International journal of environmental research and public health
Jul 12, 2018
: Dehydration may affect cognitive performances as water accounts for 75% of brain mass. The purpose of this study is to investigate the effects of dehydration and water supplementation on cognitive performances, and to explore the changes of brain s...
PURPOSE: To test if the proposed deep learning based denoising method denoising convolutional neural networks (DnCNN) with residual learning and multi-channel strategy can denoise three dimensional MR images with Rician noise robustly.
OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete response (rCR) is a poor predictor of pathologic complete response (pCR) of the axilla. We developed a convolutional neural network (CNN) algorithm to b...
One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a method to infer voxel-level transformation from higher-level correspo...
Recent advances in machine learning allow faster training, improved performance and increased interpretability of classification techniques. Consequently, their application in neuroscience is rapidly increasing. While classification approaches have p...
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