AIMC Topic:
Image Interpretation, Computer-Assisted
Clear Filters Showing 1651 to 1660 of 2744 articles
Using a deep learning system in endoscopy for screening of early esophageal squamous cell carcinoma (with video).
Gastrointestinal endoscopy
Jul 11, 2019
BACKGROUND AND AIMS: Few artificial intelligence-based technologies have been developed to improve the efficiency of screening for esophageal squamous cell carcinoma (ESCC). Here, we developed and validated a novel system of computer-aided detection ...
DeepHarmony: A deep learning approach to contrast harmonization across scanner changes.
Magnetic resonance imaging
Jul 10, 2019
Magnetic resonance imaging (MRI) is a flexible medical imaging modality that often lacks reproducibility between protocols and scanners. It has been shown that even when care is taken to standardize acquisitions, any changes in hardware, software, or...
Creating the Black Box: A Primer on Convolutional Neural Network Use in Image Interpretation.
Current problems in diagnostic radiology
Jul 9, 2019
Convolutional neural networks have been shown to demonstrate high diagnostic performance in radiologic image interpretation tasks ranging from recognition of acute stroke on computed tomography to identification of tuberculosis on plain radiographs. ...
A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jul 9, 2019
Compressed sensing (CS) theory can accelerate multi-contrast magnetic resonance imaging (MRI) by sampling fewer measurements within each contrast. However, conventional optimization-based reconstruction models suffer several limitations, including a ...
Management of Thyroid Nodules Seen on US Images: Deep Learning May Match Performance of Radiologists.
Radiology
Jul 9, 2019
BackgroundManagement of thyroid nodules may be inconsistent between different observers and time consuming for radiologists. An artificial intelligence system that uses deep learning may improve radiology workflow for management of thyroid nodules.Pu...
Multi-proportion channel ensemble model for retinal vessel segmentation.
Computers in biology and medicine
Jul 9, 2019
OBJECTIVE: A novel supervised method that is based on the Multi-Proportion Channel Ensemble Model (MPC-EM) is proposed to obtain more vessel details with reduced computational complexity.
A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection.
IEEE transactions on medical imaging
Jul 8, 2019
Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have recently been proposed for automatic glaucoma detection based on fundus images. However, none of the existing approaches can efficiently remove high redundancy in...
Automated spectrographic seizure detection using convolutional neural networks.
Seizure
Jul 8, 2019
PURPOSE: Non-convulsive seizures are common in critically ill patients, and delays in diagnosis contribute to increased morbidity and mortality. Many intensive care units employ continuous EEG (cEEG) for seizure monitoring. Although cEEG is continuou...
Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning.
Proceedings of the National Academy of Sciences of the United States of America
Jul 8, 2019
Metastasis of solid tumors is a key determinant of cancer patient survival. Targeting micrometastases using nanoparticles could offer a way to stop metastatic tumor growth before it causes excessive patient morbidity. However, nanoparticle delivery t...
Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization.
PloS one
Jul 8, 2019
PURPOSE: To develop and validate a classifier system for prediction of prostate cancer (PCa) Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w), diffusion weighted imaging (DWI) acquired using high b values, and T2-m...
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