AIMC Topic:
Image Interpretation, Computer-Assisted
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Automation, machine learning, and artificial intelligence in echocardiography: A brave new world.
Echocardiography (Mount Kisco, N.Y.)
Jul 5, 2018
Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to impro...
RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation.
IEEE journal of biomedical and health informatics
Jul 3, 2018
The level set based deformable models (LDM) are commonly used for medical image segmentation. However, they rely on a handcrafted curve evolution velocity that needs to be adapted for each segmentation task. The Convolutional Neural Networks (CNN) ad...
Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Jun 29, 2018
Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide compl...
Deep Learning Global Glomerulosclerosis in Transplant Kidney Frozen Sections.
IEEE transactions on medical imaging
Jun 27, 2018
Transplantable kidneys are in very limited supply. Accurate viability assessment prior to transplantation could minimize organ discard. Rapid and accurate evaluation of intra-operative donor kidney biopsies is essential for determining which kidneys ...
Weakly Supervised Biomedical Image Segmentation by Reiterative Learning.
IEEE journal of biomedical and health informatics
Jun 25, 2018
Recent advances in deep learning have produced encouraging results for biomedical image segmentation; however, outcomes rely heavily on comprehensive annotation. In this paper, we propose a neural network architecture and a new algorithm, known as ov...
Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound.
IEEE transactions on medical imaging
Jun 25, 2018
Temporal enhanced ultrasound (TeUS), comprising the analysis of variations in backscattered signals from a tissue over a sequence of ultrasound frames, has been previously proposed as a new paradigm for tissue characterization. In this paper, we prop...
Gastric Pathology Image Classification Using Stepwise Fine-Tuning for Deep Neural Networks.
Journal of healthcare engineering
Jun 21, 2018
Deep learning using convolutional neural networks (CNNs) is a distinguished tool for many image classification tasks. Due to its outstanding robustness and generalization, it is also expected to play a key role to facilitate advanced computer-aided d...
Advances in the computational and molecular understanding of the prostate cancer cell nucleus.
Journal of cellular biochemistry
Jun 20, 2018
Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that may not be visually perceptible to a pathologist, to the nucleus and its ultrastructural components ...
Sparse Multiview Task-Centralized Ensemble Learning for ASD Diagnosis Based on Age- and Sex-Related Functional Connectivity Patterns.
IEEE transactions on cybernetics
Jun 19, 2018
Autism spectrum disorder (ASD) is an age- and sex-related neurodevelopmental disorder that alters the brain's functional connectivity (FC). The changes caused by ASD are associated with different age- and sex-related patterns in neuroimaging data. Ho...
Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.
Gastroenterology
Jun 18, 2018
BACKGROUND & AIMS: The benefit of colonoscopy for colorectal cancer prevention depends on the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate, which is estimated to be higher than 50% in the screening-age population. ...
Predictive Value of Tests
Area Under Curve
Feasibility Studies
Diagnosis, Computer-Assisted
ROC Curve
Early Detection of Cancer
Observer Variation
Adenomatous Polyps
Colonic Polyps
Video Recording
Image Interpretation, Computer-Assisted
Humans
Neural Networks, Computer
Machine Learning
Colorectal Neoplasms
Colonoscopy
Prognosis
Reproducibility of Results
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