The classification of esophageal disease based on gastroscopic images is important in the clinical treatment, and is also helpful in providing patients with follow-up treatment plans and preventing lesion deterioration. In recent years, deep learning...
Imaging sonar systems are widely used for monitoring fish behavior in turbid or low ambient light waters. For analyzing fish behavior in sonar images, fish segmentation is often required. In this paper, Mask R-CNN is adopted for segmenting fish in so...
Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and...
Physical and engineering sciences in medicine
Nov 15, 2021
COVID-19 is an infectious disease, which has adversely affected public health and the economy across the world. On account of the highly infectious nature of the disease, rapid automated diagnosis of COVID-19 is urgently needed. A few recent findings...
IEEE journal of biomedical and health informatics
Nov 5, 2021
The coronavirus disease 2019 (COVID-19) has become a severe worldwide health emergency and is spreading at a rapid rate. Segmentation of COVID lesions from computed tomography (CT) scans is of great importance for supervising disease progression and ...
Many clinical studies follow patients over time and record the time until the occurrence of an event of interest (e.g., recovery, death, …). When patients drop out of the study or when their event did not happen before the study ended, the collected ...
Machine-assisted pathological recognition has been focused on supervised learning (SL) that suffers from a significant annotation bottleneck. We propose a semi-supervised learning (SSL) method based on the mean teacher architecture using 13,111 whole...
IEEE transactions on neural networks and learning systems
Oct 27, 2021
Conventional artificial neural network (ANN) learning algorithms for classification tasks, either derivative-based optimization algorithms or derivative-free optimization algorithms work by training ANN first (or training and validating ANN) and then...
Neural networks : the official journal of the International Neural Network Society
Oct 21, 2021
We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm. ICT encourages the prediction at an interpolation of unlabeled points to b...
The large number of poststroke recovery patients poses a burden on rehabilitation centers, hospitals, and physiotherapists. The advent of rehabilitation robotics and automated assessment systems can ease this burden by assisting in the rehabilitation...