Studies in health technology and informatics
Jan 1, 2017
This paper mainly focuses on the deep learning application in classifying the stage of diabetic retinopathy and detecting the laterality of the eye using funduscopic images. Diabetic retinopathy is a chronic, progressive, sight-threatening disease of...
Studies in health technology and informatics
Jan 1, 2017
This paper proposes an automatic classification method to detect glaucoma in fundus images. The method is based on training a neural network using public image databases. The network used in this paper is the GoogLeNet, adapted for this proposal. The...
BACKGROUND: The clinical magnetic resonance imaging (MRI) images may get corrupted due to the presence of the mixture of different types of noises such as Rician, Gaussian, impulse, etc. Most of the available filtering algorithms are noise specific, ...
Radiographics : a review publication of the Radiological Society of North America, Inc
Jan 1, 2017
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapp...
Journal of X-ray science and technology
Jan 1, 2017
Digital radiography system is widely used for noninvasive security check and medical imaging examination. However, the system has a limitation of lower image quality in spatial resolution and signal to noise ratio. In this study, we explored whether ...
Advances in experimental medicine and biology
Jan 1, 2017
Emotion recognition plays an important role in several applications, such as human computer interaction and understanding affective state of users in certain tasks, e.g., within a learning process, monitoring of elderly, interactive entertainment etc...
A large number of dissolution data were measured and integrated into a previously constructed tablet database composed of 14 kinds of compounds as model active pharmaceutical ingredients (APIs) with contents ranging from 10 to 80%. The database has c...
Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of f...
Studies in health technology and informatics
Jan 1, 2017
Fine-meshed perioperative measurements are offering enormous potential for automatically investigating clinical complications during general anesthesia. In this study, we employed multiple machine learning methods to model perioperative hypoxia and c...
Studies in health technology and informatics
Jan 1, 2017
The purpose of this work is to evaluate methods from deep learning for application to Magnetic Resonance Fingerprinting (MRF). MRF is a recently proposed measurement technique for generating quantitative parameter maps. In MRF a non-steady state sign...
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