As more images are acquired and read digitally, difficulty often arises in using these images for conferences and presentations. Most digital images are in DICOM format, which cannot be used by presentation software such as Microsoft PowerPoint, and
As more images are acquired and read digitally, difficulty often arises in using these images for conferences and presentations.
Most digital images are in DICOM format, which cannot be used by presentation software such as Microsoft PowerPoint, and many radiologists lack the ability to manipulate the images on their desktops. DICOM images are also too large to handle conveniently without conversion to a smaller format.
Some PACS can convert DICOM images into other formats, but radiologists who lack this capability can use software freely available on the Internet to manipulate and view the images on PCs.
An educational exhibit presented by Dr. Edward J. Escott, an assistant professor of radiology at the University of Colorado, described a number of these programs, compared their features, and suggested which are best suited for particular purposes.
Escott searched the Web for free DICOM viewing or processing software, selecting those he believed to be user-friendly and compatible with Windows platforms.
The wide variety of programs available fall into three basic categories:
"Some of the programs in the last category are primarily designed for general use and also have the ability to work with DICOM images," Escott said.
A few programs provide all the features needed so that almost any DICOM image can be cropped, appropriately windowed, and possibly annotated in a PC-friendly format for presentation programs or on the Web. They include Osiris, FP Image (trial version), Xn View, IrfanView32, and Imread.
Burnout in Radiology: Key Risk Factors and Promising Solutions
June 9th 2025Recognizing the daunting combination of increasing imaging volume and workforce shortages, these authors discuss key risk factors contributing to burnout and moral injury in radiology, and potential solutions to help preserve well-being among radiologists.
Study: AI-Generated ADC Maps from MRI More Than Double Specificity in Prostate Cancer Detection
June 5th 2025Emerging research showed that AI-generated ADC mapping from MRI led to significant increases in accuracy, PPV and specificity in comparison to conventional ADC mapping while achieving a 93 percent sensitivity for PCa.