AccuSoft adds browser extension to product linePushing forward with its medical imaging software suite, developer AccuSoft last month introduced ExamiNet V1.0, a new Web-browser extension developed for medical schools and teleradiology firms.
Pushing forward with its medical imaging software suite, developer AccuSoft last month introduced ExamiNet V1.0, a new Web-browser extension developed for medical schools and teleradiology firms. ExamiNet allows users to view and manipulate DICOM 3.0 images on the Internet by loading the images onto an HTML, Netscape, or Internet Explorer page.
With ExamiNet, users can incorporate DICOM 3.0 images into Web sites or presentations and save them as any of seven file formats, including TIFF, JPEG, BMP, DCX, TGA, PCX, and PNG. The saved images can be used in other software packages like Power Point or Harvard Graphics, according to AccuSoft.
The company will support any new DICOM image formats through its Image Guarantee: If AccuSoft's toolkit software is unable to read an image, users can send the image to the company, and engin- eers will create a patch to support the image free of charge. The firm expected ExamiNet to be available by the end of January.
Other offerings in the Westborough, MA-based firm's product line include DICOM Communications SDK (PNN 5/98), a kit that allows developers to write software code that bridges medical imaging devices.
Another product, Medical Imaging SDK, interprets DICOM data once they are received. ExamiNet is the next generation of AccuSoft's DICOM Netscape Plug-In.
Study Reaffirms Low Risk for csPCa with Biopsy Omission After Negative Prostate MRI
December 19th 2024In a new study involving nearly 600 biopsy-naïve men, researchers found that only 4 percent of those with negative prostate MRI had clinically significant prostate cancer after three years of active monitoring.
Study Examines Impact of Deep Learning on Fast MRI Protocols for Knee Pain
December 17th 2024Ten-minute and five-minute knee MRI exams with compressed sequences facilitated by deep learning offered nearly equivalent sensitivity and specificity as an 18-minute conventional MRI knee exam, according to research presented recently at the RSNA conference.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.