BACKGROUND: Functional transcranial Doppler (fTCD) is an ultrasound based neuroimaging technique used to assess neural activation that occurs during a cognitive task through measuring velocity of cerebral blood flow.
Alzheimer's disease (AD) has been not only a substantial financial burden to the health care system but also an emotional burden to patients and their families. Making accurate diagnosis of AD based on brain magnetic resonance imaging (MRI) is becomi...
Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segme...
During routine ultrasound assessment of the fetal brain for biometry estimation and detection of fetal abnormalities, accurate imaging planes must be found by sonologists following a well-defined imaging protocol or clinical standard, which can be di...
Medical & biological engineering & computing
Sep 26, 2017
Precise segmentation of stroke lesions from brain magnetic resonance (MR) images poses a challenging task in automated diagnosis. In this paper, we proposed a new method called watershed-based lesion segmentation algorithm (WLSA), which is a novel in...
There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiologic...
The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data whe...
Accurate and robust tomographic reconstruction from dynamic positron emission tomography (PET) acquired data is a difficult problem. Conventional methods, such as the maximum likelihood expectation maximization (MLEM) algorithm for reconstructing the...
Early intervention strategies in psychosis would significantly benefit from the identification of reliable prognostic biomarkers. Pattern classification methods have shown the feasibility of an early diagnosis of psychosis onset both in clinical and ...
Computational intelligence and neuroscience
Sep 19, 2017
This paper proposes two multimodal fusion methods between brain and peripheral signals for emotion recognition. The input signals are electroencephalogram and facial expression. The stimuli are based on a subset of movie clips that correspond to four...
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