Computer methods and programs in biomedicine
Mar 15, 2020
OBJECTIVE: Herein, a neural network-based liver segmentation algorithm is proposed, and its performance was evaluated using abdominal computed tomography (CT) images.
In this research, we present a semi-supervised segmentation solution using convolutional autoencoders to solve the problem of segmentation tasks having a small number of ground-truth images. We evaluate the proposed deep network architecture for the ...
Chest radiography (CXR) is the most commonly used imaging modality and deep neural network (DNN) algorithms have shown promise in effective triage of normal and abnormal radiograms. Typically, DNNs require large quantities of expertly labelled traini...
This paper proposes a new supervised method for blood vessel segmentation using Zernike moment-based shape descriptors. The method implements a pixel wise classification by computing a 11-D feature vector comprising of both statistical (gray-level) f...
Early detection of breast cancer and its correct stage determination are important for prognosis and rendering appropriate personalized clinical treatment to breast cancer patients. However, despite considerable efforts and progress, there is a need ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Patient perceptions of wait time during outpatient office visits can affect patient satisfaction. Providing accurate information about wait times could improve patients' satisfaction by reducing uncertainty. However, these are rarely known about effi...
PURPOSE: Segmentation of left ventricular myocardium (LVM) in coronary computed tomography angiography (CCTA) is important for diagnosis of cardiovascular diseases. Due to poor image contrast and large variation in intensity and shapes, LVM segmentat...
IEEE journal of biomedical and health informatics
Feb 28, 2020
Ischemic stroke is a major cause of death and disability in adulthood worldwide. Because it has highly heterogeneous phenotypes, phenotyping of ischemic stroke is an essential task for medical research and clinical prognostication. However, this task...
The advancement of glass science has played a pivotal role in enhancing the quality and length of human life. However, with an ever-increasing demand for glasses in a variety of healthcare applications - especially with controlled degradation rates -...
Neural networks : the official journal of the International Neural Network Society
Feb 26, 2020
Deep neural networks (DNNs) have been very successful for supervised learning. However, their high generalization performance often comes with the high cost of annotating data manually. Collecting low-quality labeled dataset is relatively cheap, e.g....