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Radiography, Abdominal

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Assessment of Critical Feeding Tube Malpositions on Radiographs Using Deep Learning.

Journal of digital imaging
Assess the efficacy of deep convolutional neural networks (DCNNs) in detection of critical enteric feeding tube malpositions on radiographs. 5475 de-identified HIPAA compliant frontal view chest and abdominal radiographs were obtained, consisting of ...

LEARN: Learned Experts' Assessment-Based Reconstruction Network for Sparse-Data CT.

IEEE transactions on medical imaging
Compressive sensing (CS) has proved effective for tomographic reconstruction from sparsely collected data or under-sampled measurements, which are practically important for few-view computed tomography (CT), tomosynthesis, interior tomography, and so...

Automated Radiology Report Summarization Using an Open-Source Natural Language Processing Pipeline.

Journal of digital imaging
Diagnostic radiologists are expected to review and assimilate findings from prior studies when constructing their overall assessment of the current study. Radiology information systems facilitate this process by presenting the radiologist with a subs...

Deep Convolutional Neural Networks for Endotracheal Tube Position and X-ray Image Classification: Challenges and Opportunities.

Journal of digital imaging
The goal of this study is to evaluate the efficacy of deep convolutional neural networks (DCNNs) in differentiating subtle, intermediate, and more obvious image differences in radiography. Three different datasets were created, which included presenc...

Histogram-Based Discrimination of Intravenous Contrast in Abdominopelvic Computed Tomography.

Journal of computer assisted tomography
OBJECTIVE: The aim of this study was to evaluate the accuracy of fully automated machine learning methods for detecting intravenous contrast in computed tomography (CT) studies of the abdomen and pelvis.

Automatic anatomy recognition in whole-body PET/CT images.

Medical physics
PURPOSE: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is...

Follow-up Recommendation Detection on Radiology Reports with Incidental Pulmonary Nodules.

Studies in health technology and informatics
The management of follow-up recommendations is fundamental for the appropriate care of patients with incidental pulmonary findings. The lack of communication of these important findings can result in important actionable information being lost in hea...

Identification of Incidental Pulmonary Nodules in Free-text Radiology Reports: An Initial Investigation.

Studies in health technology and informatics
Advances in image quality produced by computed tomography (CT) and the growth in the number of image studies currently performed has made the management of incidental pulmonary nodules (IPNs) a challenging task. This research aims to identify IPNs in...