The Content of these Video Presentations have not been submitted to FDA. The observations made in these Videos are based on the personal experiece of Radiologists.
Publications
Potential for Dose Reduction in CT Emphysema Densitometry with Post-Scan Noise Reduction: A Phantom Study
This research paper was published in the British Journal of Radiology in 2020.
Iterative Reconstruction and Deep Learning Algorithms for Enabling Low Dose Computed Tomography in Midfacial Trauma
This is a pre-proof of a paper called “Iterative Reconstruction and Deep Learning Algorithms for Enabling Low Dose Computed Tomography in Midfacial Trauma” in Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology.
Let’s Reassess Radiological Patient Safety, Radiation, and CT Image Quality
One of the main goals of diagnostic radiology is to acquire high-quality images with a low dose of radiation, as high-quality images enable radiologists to make meaningful diagnoses, and low doses of radiation keep patients safe. But what exactly defines a “low-dose CT scan”? Understanding radiation dosage can be complicated, even for radiologists.
Achieving ALARA - Why are CT Scan Patients Exposed to So Much Radiation?
As low as reasonably achievable, or ALARA, is a goal in radiation safety. PixelShine® offers a technically feasible way to reduce radiation exposure within economic constraints—making it a must-have for providers seeking to achieve ALARA.
Why Clinical Confidence is So Important in Diagnostic Radiology
An estimated 251,000 patients in the United States die yearly due to medical errors, making it a leading cause of death. As such, the fear of missing or incorrectly attributing medical diagnostic findings is a valid one. Within radiology specifically, studies have shown an error rate of 33% on positive studies—or 4% overall error rate across all studies seen in a day—which amounts to 40 million interpretive errors yearly worldwide.
What some recent clients say about their experience with Algomedica. ‘Quotations provided are not scientifically proven’
Fabulous, very impressive and I am looking forward to using it in my clinic
PixelShine is the type of AI technology that clinicians should be leveraging to improve patient care and reduce radiation dose. PixelShine enables radiology to push the boundaries of technology to minimize radiation risk to our patients.
PixelShine processing of filtered back projection images creates higher quality studies, in a fraction of the time, than our CT scanner can produce with its most recent generation of iterative reconstruction. It is a monumental achievement.
You nailed it when it comes to lung parenchyma! Higher dose reduction, better noise reduction, edges better defined, no artifacts.
“Machine learning tools like PixelShine have the potential to expand low dose CT beyond pediatrics and lung screening. PixelShine could make low dose imaging routine for all applications.”
PixelShine from AlgoMedica is a revolutionary tool in image processing and allows for substantially reduced radiation dose.
Fabulous, very impressive and I am looking forward to using it in my clinic
PixelShine is the type of AI technology that clinicians should be leveraging to improve patient care and reduce radiation dose. PixelShine enables radiology to push the boundaries of technology to minimize radiation risk to our patients.
If you- have older scanners, screen asymptomatic persons for lung cancer, scan obese patients, conduct pediatric scans- want to offer high quality scans