AIMC Topic:
Image Interpretation, Computer-Assisted

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Fully Convolutional DenseNet with Multiscale Context for Automated Breast Tumor Segmentation.

Journal of healthcare engineering Jan 14, 2019
Breast tumor segmentation plays a crucial role in subsequent disease diagnosis, and most algorithms need interactive prior to firstly locate tumors and perform segmentation based on tumor-centric candidates. In this paper, we propose a fully convolut...
Humans Breast Neoplasms Neural Networks, Computer Mammography Breast Algorithms Image Interpretation, Computer-Assisted Female
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Improving the Quality of Synthetic FLAIR Images with Deep Learning Using a Conditional Generative Adversarial Network for Pixel-by-Pixel Image Translation.

AJNR. American journal of neuroradiology Jan 10, 2019
BACKGROUND AND PURPOSE: Synthetic FLAIR images are of lower quality than conventional FLAIR images. Here, we aimed to improve the synthetic FLAIR image quality using deep learning with pixel-by-pixel translation through conditional generative adversa...
Female Artifacts Humans Adult Neuroimaging Software Deep Learning Male Brain Magnetic Resonance Imaging Middle Aged Image Interpretation, Computer-Assisted
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Knowledge-Aided Convolutional Neural Network for Small Organ Segmentation.

IEEE journal of biomedical and health informatics Jan 9, 2019
Accurate and automatic organ segmentation is critical for computer-aided analysis towards clinical decision support and treatment planning. State-of-the-art approaches have achieved remarkable segmentation accuracy on large organs, such as the liver ...
Image Interpretation, Computer-Assisted Humans Algorithms Pancreas Adrenal Glands Tomography, X-Ray Computed Neural Networks, Computer Gallbladder Fuzzy Logic
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Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network.

World journal of surgical oncology Jan 8, 2019
BACKGROUND: In this study, images of 2450 benign thyroid nodules and 2557 malignant thyroid nodules were collected and labeled, and an automatic image recognition and diagnosis system was established by deep learning using the YOLOv2 neural network. ...
Predictive Value of Tests Adult Image Interpretation, Computer-Assisted Male Middle Aged Thyroid Gland Ultrasonography Retrospective Studies Thyroid Nodule Humans Female ROC Curve Neural Networks, Computer Diagnosis, Differential Aged Prognosis Young Adult
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Fast ScanNet: Fast and Dense Analysis of Multi-Gigapixel Whole-Slide Images for Cancer Metastasis Detection.

IEEE transactions on medical imaging Jan 7, 2019
Lymph node metastasis is one of the most important indicators in breast cancer diagnosis, that is traditionally observed under the microscope by pathologists. In recent years, with the dramatic advance of high-throughput scanning and deep learning te...
Humans Algorithms Deep Learning Lymph Nodes Lymphatic Metastasis Image Interpretation, Computer-Assisted Histocytochemistry
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Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jan 7, 2019
BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning ha...
Automation Proof of Concept Study Blood Flow Velocity Aorta Predictive Value of Tests Heart Diseases Image Interpretation, Computer-Assisted Myocardial Perfusion Imaging Magnetic Resonance Imaging, Cine Reproducibility of Results Aged Male Middle Aged Hemodynamics United States Aortic Valve Machine Learning Prospective Studies Retrospective Studies Female Humans
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Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

La Radiologia medica Jan 3, 2019
OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate canc...
Machine Learning Prospective Studies Aged Aged, 80 and over Humans Neoplasm Grading Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Male Predictive Value of Tests Radiotherapy, Intensity-Modulated Middle Aged Prostatic Neoplasms Treatment Outcome Neoplasm Staging
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A Deep Learning-Based Approach to Reduce Rescan and Recall Rates in Clinical MRI Examinations.

AJNR. American journal of neuroradiology Jan 3, 2019
BACKGROUND AND PURPOSE: MR imaging rescans and recalls can create large hospital revenue loss. The purpose of this study was to develop a fast, automated method for assessing rescan need in motion-corrupted brain series.
Artifacts Humans Neuroimaging Brain Deep Learning Female Magnetic Resonance Imaging Male Image Interpretation, Computer-Assisted
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Classification and Quantification of Emphysema Using a Multi-Scale Residual Network.

IEEE journal of biomedical and health informatics Jan 1, 2019
Automated tissue classification is an essential step for quantitative analysis and treatment of emphysema. Although many studies have been conducted in this area, there still remain two major challenges. First, different emphysematous tissue appears ...
Humans Algorithms Lung Tomography, X-Ray Computed Deep Learning Aged Pulmonary Emphysema Adult Image Interpretation, Computer-Assisted Middle Aged
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Deep structure tensor graph search framework for automated extraction and characterization of retinal layers and fluid pathology in retinal SD-OCT scans.

Computers in biology and medicine Dec 31, 2018
Maculopathy is a group of retinal disorders that affect macula and cause severe visual impairment if not treated in time. Many computer-aided diagnostic methods have been proposed over the past that automatically detect macular diseases. However, to ...
Retina Macular Degeneration Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Tomography, Optical Coherence
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