- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
AccuImage names new CEO
Robert Taylor has been appointed CEO of AccuImage, a South San Francisco, CA-based developer of 3-D and 4-D post-processing and connectivity software for PACS and other medical imaging applications. Taylor, previously COO of AccuImage, replaces Allen
Robert Taylor has been appointed CEO of AccuImage, a South San Francisco, CA-based developer of 3-D and 4-D post-processing and connectivity software for PACS and other medical imaging applications. Taylor, previously COO of AccuImage, replaces Allen Poirson, who resigned from the company.
AccuImage expects Taylors appointment to help expedite AccuImages current product development efforts, which include AccuView, a 3-D workstation, and eStation 3D, a Web-based workstation for PACS and teleradiology. Taylor will be responsible for moving AccuView into the marketplace and overseeing final development of eStation 3D, according to Douglas Boyd, chairman of AccuImage. Both products incorporate AccuImages proprietary software platform, which provides review and analysis tools for CT, MR, and ultrasound imaging and enables the transfer of medical images across the Internet and hospital intranets.
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.
