The International journal of eating disorders
Aug 21, 2018
OBJECTIVE: Emotional eating has been linked to ovarian hormone functioning, but no studies to-date have considered the role of brain function. This knowledge gap may stem from methodological challenges: Data are heterogeneous, violating assumptions o...
A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of Alzheimer's disease (AD). However, while the vast majority of these works use the public dataset ADNI for evaluation, they ...
INTRODUCTION: The main goal of this work is to investigate the feasibility of estimating an anatomical index that can be used as an Alzheimer's disease (AD) risk factor in the Women's Health Initiative Magnetic Resonance Imaging Study (WHIMS-MRI) usi...
Breast tumor segmentation based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging problem and an active area of research. Particular challenges, similarly as in other segmentation problems, include the class-imbalance...
IEEE transactions on bio-medical engineering
Aug 15, 2018
OBJECTIVE: The aim of this paper is to describe an automated diagnostic pipeline that uses as input only ultrasound (US) data, but is at the same time informed by a training database of multimodal magnetic resonance (MR) and US image data.
Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Aug 14, 2018
Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provides superior soft tissue contrast without ionizing radiation compared with computed tomography (CT). However, it requires the generation of pseudo CT f...
IEEE journal of biomedical and health informatics
Aug 14, 2018
In this paper, we present a novel convolutional neural network architecture to segment images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed model is an extension of the U-net that embeds a cardiac shape prior and ...
We introduce a model-based image reconstruction framework with a convolution neural network (CNN)-based regularization prior. The proposed formulation provides a systematic approach for deriving deep architectures for inverse problems with the arbitr...
International journal of computer assisted radiology and surgery
Aug 11, 2018
PURPOSE: This paper presents new quantitative data on a signal-to-noise ratio (SNR) study, distortion study, and targeting accuracy phantom study for our patient-mounted robot (called Arthrobot). Arthrobot was developed as an MRI-guided needle placem...
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