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Radiology Information Systems

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Detection and Labeling of Vertebrae in MR Images Using Deep Learning with Clinical Annotations as Training Data.

Journal of digital imaging
The purpose of this study was to investigate the potential of using clinically provided spine label annotations stored in a single institution image archive as training data for deep learning-based vertebral detection and labeling pipelines. Lumbar a...

Modeling a System for Generating Structured Reports.

Studies in health technology and informatics
The purpose of this research is to make the medical report generation process more practical, fast and reliable, both for the health professional and for the patient. We created an ontology and modeling of a structured report (SR) Standard DICOM SR.

An Ontology-Based Approach to Estimate the Frequency of Rare Diseases in Narrative-Text Radiology Reports.

Studies in health technology and informatics
This study sought to use ontology-based knowledge to identify patients with rare diseases and to estimate the frequency of those diseases in a large database of radiology reports. Natural language processing methods were applied to 12,377,743 narrari...

Deep Learning: A Primer for Radiologists.

Radiographics : a review publication of the Radiological Society of North America, Inc
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapp...

Correlate: A PACS- and EHR-integrated Tool Leveraging Natural Language Processing to Provide Automated Clinical Follow-up.

Radiographics : a review publication of the Radiological Society of North America, Inc
A major challenge for radiologists is obtaining meaningful clinical follow-up information for even a small percentage of cases encountered and dictated. Traditional methods, such as keeping medical record number follow-up lists, discussing cases with...

Natural Language Processing in Radiology: A Systematic Review.

Radiology
Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are st...

Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO.

Technology and health care : official journal of the European Society for Engineering and Medicine
It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal...

Unsupervised Topic Modeling in a Large Free Text Radiology Report Repository.

Journal of digital imaging
Radiology report narrative contains a large amount of information about the patient's health and the radiologist's interpretation of medical findings. Most of this critical information is entered in free text format, even when structured radiology re...

A Statistical Analysis of Term Occurrences in Radiology Reporting.

Studies in health technology and informatics
To compare term occurrences in free-text radiology reports and RSNA reporting templates, we selected five templates from an RSNA reporting template library and their corresponding free-text reports as a test set, and employed the Wilcoxon signed-rank...