AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks.

Journal of digital imaging Oct 1, 2019
Our objective is to evaluate the effectiveness of efficient convolutional neural networks (CNNs) for abnormality detection in chest radiographs and investigate the generalizability of our models on data from independent sources. We used the National ...
Humans Neural Networks, Computer Female Radiographic Image Interpretation, Computer-Assisted Lung Diseases Datasets as Topic Radiography, Thoracic Male Middle Aged Deep Learning
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Development of an Artificially Intelligent Mobile Phone Application to Identify Cardiac Devices on Chest Radiography.

JACC. Clinical electrophysiology Sep 1, 2019
Radiography, Thoracic Defibrillators, Implantable Pacemaker, Artificial Humans Artificial Intelligence Mobile Applications Radiographic Image Interpretation, Computer-Assisted
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[Research progress on computed tomography image detection and classification of pulmonary nodule based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2019
Computer-aided diagnosis based on computed tomography (CT) image can realize the detection and classification of pulmonary nodules, and improve the survival rate of early lung cancer, which has important clinical significance. In recent years, with t...
Radiographic Image Interpretation, Computer-Assisted Deep Learning Humans Lung Neoplasms Tomography, X-Ray Computed Solitary Pulmonary Nodule Reproducibility of Results
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Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.

Journal of digital imaging Aug 1, 2019
Machine learning has several potential uses in medical imaging for semantic labeling of images to improve radiologist workflow and to triage studies for review. The purpose of this study was to (1) develop deep convolutional neural networks (DCNNs) f...
Semantics Humans Machine Learning Mammography Female Radiographic Image Interpretation, Computer-Assisted Breast Neoplasms Breast Deep Learning
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The Classification of Renal Cancer in 3-Phase CT Images Using a Deep Learning Method.

Journal of digital imaging Aug 1, 2019
In this research, we exploit an image-based deep learning framework to distinguish three major subtypes of renal cell carcinoma (clear cell, papillary, and chromophobe) using images acquired with computed tomography (CT). A biopsy-proven benchmarking...
Kidney Neoplasms Carcinoma, Renal Cell Humans Tomography, X-Ray Computed Deep Learning Republic of Korea Reproducibility of Results Kidney Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted
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Improved Cancer Detection Using Artificial Intelligence: a Retrospective Evaluation of Missed Cancers on Mammography.

Journal of digital imaging Aug 1, 2019
To determine whether cmAssist™, an artificial intelligence-based computer-aided detection (AI-CAD) algorithm, can be used to improve radiologists' sensitivity in breast cancer screening and detection. A blinded retrospective study was performed with ...
Reproducibility of Results Aged Aged, 80 and over Adult Sensitivity and Specificity Breast Neoplasms Artificial Intelligence Retrospective Studies Female Humans Breast Middle Aged False Negative Reactions Mammography Radiographic Image Interpretation, Computer-Assisted
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Ankle Fracture Detection Utilizing a Convolutional Neural Network Ensemble Implemented with a Small Sample, De Novo Training, and Multiview Incorporation.

Journal of digital imaging Aug 1, 2019
To determine whether we could train convolutional neural network (CNN) models de novo with a small dataset, a total of 596 normal and abnormal ankle cases were collected and processed. Single- and multiview models were created to determine the effect...
Neural Networks, Computer Humans Sensitivity and Specificity Radiography Ankle Radiographic Image Interpretation, Computer-Assisted Ankle Fractures Datasets as Topic
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Automated segmentation and quantification of aortic calcification at abdominal CT: application of a deep learning-based algorithm to a longitudinal screening cohort.

Abdominal radiology (New York) Aug 1, 2019
OBJECTIVE: To investigate an automated aortic calcium segmentation and scoring tool at abdominal CT in an adult screening cohort.
Vascular Calcification Aortic Diseases Radiography, Abdominal Middle Aged Deep Learning Mass Screening Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Aorta, Abdominal Aged Adult Male Humans Tomography, X-Ray Computed Female
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Reduction of False-Positive Markings on Mammograms: a Retrospective Comparison Study Using an Artificial Intelligence-Based CAD.

Journal of digital imaging Aug 1, 2019
The aim was to determine whether an artificial intelligence (AI)-based, computer-aided detection (CAD) software can be used to reduce false positive per image (FPPI) on mammograms as compared to an FDA-approved conventional CAD. A retrospective study...
Humans Artificial Intelligence Retrospective Studies Mammography Radiographic Image Interpretation, Computer-Assisted Breast False Positive Reactions Female Sensitivity and Specificity Breast Neoplasms
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Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network.

Journal of digital imaging Aug 1, 2019
The Deep Convolutional Neural Network (DCNN) is one of the most powerful and successful deep learning approaches. DCNNs have already provided superior performance in different modalities of medical imaging including breast cancer classification, segm...
Radiographic Image Interpretation, Computer-Assisted Breast Female Humans Breast Neoplasms Neural Networks, Computer Mammography Machine Learning
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