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Dose-monitoring software tracks lowered patient dose
By Erik L. Ridley
Sunday, November 27 | 11:45 a.m.-11:55 a.m. | SSA21-07 | Room S404ABResearchers will show in this scientific presentation how they used automated dose-monitoring software to confirm that their new CT scanner offered significantly lower radiation dose for patients.
November 6, 2016
Anatomical landmarks yield patient-specific organ dose
By Erik L. Ridley
Sunday, November 27 | 11:25 a.m.-11:35 a.m. | SSA21-05 | Room S404ABIn this talk, researchers will describe how automatic measurements of patient anatomical landmarks by radiation dose-monitoring software can pave the way for patient-specific organ dosimetry.
November 6, 2016
Are CT reports transferred with trauma patients unreliable?
By Eric Barnes
Sunday, November 27 | 10:45 a.m.-10:55 a.m. | SSA06-01 | Room N226Radiologists from a level I trauma center wondered if the CT reports they were getting for patients transferred to their emergency department were accurate. Their six-month investigation didn't deliver much confidence in the original reads.
November 6, 2016
Road to RSNA 2016: Healthcare IT Preview
By Erik L. Ridley
This Road to RSNA preview takes a look at RSNA 2016's presentations on healthcare IT. Radiation dose monitoring will again be an important area of emphasis at this year's meeting. Investigators are also continuing to seek enhancements in areas related to radiology reporting and clinical decision support.
November 6, 2016
2014 11 03 11 22 44 485 Road To Rsna 200
Vital Images to buy Karos Health
By AuntMinnie.com staff writers
Advanced visualization software developer Vital Images has signed an agreement to acquire global healthcare informatics company Karos Health.
November 1, 2016
Road to RSNA 2016: Imaging Informatics Preview
By Erik L. Ridley
Welcome to the first installment of this year's Road to RSNA preview of the 2016 RSNA meeting in Chicago. For the eighth year in a row, we're providing a modality-by-modality overview of the most important scientific sessions to serve as your guide to events at McCormick Place. Our journey along the Road to RSNA begins with our preview of Imaging Informatics, and specifically PACS, deep learning, and teleradiology.
October 30, 2016
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PACS software tool boosts lesion measurement accuracy
By Erik L. Ridley
Thursday, December 1 | 11:40 a.m.-11:50 a.m. | SSQ10-08 | Room S403AIn this talk, researchers will share how a PACS-integrated software tool can help radiologists be more efficient and accurate in documenting lesion measurements.
October 30, 2016
Can display features improve DR interpretations?
By Erik L. Ridley
Wednesday, November 30 | 3:50 p.m.-4:00 p.m. | SSM12-06 | Room S403AIn this scientific presentation, an Italian group will show how higher spatial resolution and luminance levels on medical displays may be able to improve radiologist performance in reading digital radiography (DR) images.
October 30, 2016
PACS display features affect diagnostic performance
By Erik L. Ridley
Wednesday, November 30 | 3:20 p.m.-3:30 p.m. | SSM12-03 | Room S403AItalian researchers will report in this session on the display characteristics and settings that most affect the identification of cerebral infarction on brain CT exams.
October 30, 2016
Deep learning could help uncover disease biomarkers
By Erik L. Ridley
Wednesday, November 30 | 12:45 p.m.-1:15 p.m. | IN247-SD-WEB2 | Lakeside, IN Community, Station 2This poster presentation will illustrate the potential of deep-learning methods for finding imaging biomarkers in relatively uncommon diseases, such as nasopharyngeal cancer.
October 30, 2016
Deep learning can label partially annotated images
By Erik L. Ridley
Wednesday, November 30 | 12:15 p.m.-12:45 p.m. | IN242-SD-WEA3 | Lakeside, IN Community, Station 3In this poster presentation, a study team will show how deep-learning techniques can be used to fully segment and label disease regions on images that have only been partially annotated.
October 30, 2016
Deep learning can segment, measure lymph node clusters
By Erik L. Ridley
Wednesday, November 30 | 10:30 a.m.-10:40 a.m. | SSK17-01 | Room S404ABIn this scientific session, researchers will reveal how an automated method based on deep learning shows promise for segmenting and measuring the volume of lymph node clusters.
October 30, 2016
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