The applications of artificial intelligence (AI), including machine learning and deep learning, in the field of pancreatic disease imaging are rapidly expanding. AI can be used for the detection of pancreatic ductal adenocarcinoma and other pancreati...
IEEE transactions on neural networks and learning systems
Feb 4, 2021
A common shortfall of supervised deep learning for medical imaging is the lack of labeled data, which is often expensive and time consuming to collect. This article presents a new semisupervised method for medical image segmentation, where the networ...
Deep learning (DL) approaches to medical image analysis tasks have recently become popular; however, they suffer from a lack of human interpretability critical for both increasing understanding of the methods' operation and enabling clinical translat...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Medical ionizing radiation procedures and especially medical imaging are a non negligible source of exposure to patients. Whereas the biological effects of high absorbed doses are relatively well known, the effects of low absorbed doses are still deb...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Radiology reports have been widely used for extraction of various clinically significant information about patients' imaging studies. However, limited research has focused on standardizing the entities to a common radiology-specific vocabulary. Furth...
In many medical image classification tasks, there is insufficient image data for deep convolutional neural networks (CNNs) to overcome the over-fitting problem. The light-weighted CNNs are easy to train but they usually have relatively poor classific...
IEEE reviews in biomedical engineering
Jan 22, 2021
Medical image analysis methods require the use of effective representations for differentiating between lesions, diseased regions, and normal structure. Amplitude Modulation-Frequency Modulation (AM-FM) models provide effective representations throug...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 21, 2021
Instance segmentation is an important task for biomedical and biological image analysis. Due to the complicated background components, the high variability of object appearances, numerous overlapping objects, and ambiguous object boundaries, this tas...
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