Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Sep 26, 2018
This paper introduces an unsupervised adversarial similarity network for image registration. Unlike existing deep learning registration frameworks, our approach does not require ground-truth deformations and specific similarity metrics. We connect a ...
Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to compare its performance with physicians including thoracic radiologists. Materials and Methods For ...
International journal of computer assisted radiology and surgery
Sep 25, 2018
PURPOSE: With the advent of robot-assisted surgery, the role of data-driven approaches to integrate statistics and machine learning is growing rapidly with prominent interests in objective surgical skill assessment. However, most existing work requir...
Cancer communications (London, England)
Sep 25, 2018
BACKGROUND: Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal mali...
We propose a framework for localization and classification of masses in breast ultrasound images. We have experimentally found that training convolutional neural network-based mass detectors with large, weakly annotated datasets presents a non-trivia...
International journal of pharmaceutics
Sep 22, 2018
The multivariate nature of a fluidized bed system creates process complexity that increases the risk of production upset. This research explores the use of passive acoustic emissions monitoring paired with an artificial neural network to detect fluid...
IEEE journal of biomedical and health informatics
Sep 20, 2018
This paper proposes deep learning methods with signal alignment that facilitate the end-to-end classification of raw electrocardiogram (ECG) signals into heartbeat types, i.e., normal beat or different types of arrhythmias. Time-domain sample points ...
Growth/no growth boundary models for Bacillus spores that accounted for the effects of environmental pH, water activity (a), acetic acid, lactic acid, bacterial strain, and storage period were developed using conventional logistic regression and mach...
Neural networks : the official journal of the International Neural Network Society
Sep 20, 2018
As humans we possess an intuitive ability for navigation which we master through years of practice; however existing approaches to model this trait for diverse tasks including monitoring pedestrian flow and detecting abnormal events have been limited...
Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic resonance imaging (MRI) is an accurate method for determination of body fat volume and distribution. How...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.