In this paper, we propose DeepCut, a method to obtain pixelwise object segmentations given an image dataset labelled weak annotations, in our case bounding boxes. It extends the approach of the well-known GrabCut [1] method to include machine learnin...
Computational intelligence and neuroscience
Oct 31, 2016
Functional near-infrared spectroscopy (fNIRS) is suitable for noninvasive mapping of relative changes in regional cortical activity but is limited for quantitative comparisons among cortical sites, subjects, and populations. We have developed a convo...
We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation. The devised architecture is the result of an in-depth analysis of the limitations of current networks pro...
BACKGROUND: Muscle tissue saturation (StO) measured with near-infrared spectroscopy has generally been considered a measurement of the tissue microcirculatory condition. However, we hypothesized that StO could be more regarded as a fast and reliable ...
Does sense of agency (SoA) arise merely from action-outcome associations, or does an additional real-time process track each step along the chain? Tracking control predicts that deviant intermediate steps between action and outcome should reduce SoA....
INTRODUCTION: In recent years, machine-learning techniques have gained growing popularity in medical image analysis. Temporal brain-state classification is one of the major applications of machine-learning techniques in functional magnetic resonance ...
BACKGROUND: Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in hum...
An important focus of studies of individuals at ultra-high risk (UHR) for psychosis has been to identify biomarkers to predict which individuals will transition to psychosis. However, the majority of individuals will prove to be resilient and go on t...
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Oct 2, 2016
High-grade glioma (HGG) is a lethal cancer, which is characterized by very poor prognosis. To help optimize treatment strategy, accurate preoperative prediction of HGG patient's outcome (i.e., survival time) is of great clinical value. However, there...
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Oct 2, 2016
Parkinson's disease (PD) is a major progressive neurodegenerative disorder. Accurate diagnosis of PD is crucial to control the symptoms appropriately. However, its clinical diagnosis mostly relies on the subjective judgment of physicians and the clin...
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