Deal parallels those with Siemens and DiasonicsALI Technologies is solidifying its position as the preferredchoice for ultrasound vendors who want access to an ultrasounddigital image management system but don't want to develop oneon their own.
ALI Technologies is solidifying its position as the preferredchoice for ultrasound vendors who want access to an ultrasounddigital image management system but don't want to develop oneon their own. The Richmond, British Columbia, company last weekannounced that it will provide its UltraPACS product to GE MedicalSystems of Milwaukee on a joint marketing basis.
The deal, which was announced at the American Institute ofUltrasound in Medicine meeting in New York City, is similar toan arrangement signed with Siemens last year (SCAN 8/2/95), accordingto Greg Peet, ALI's CEO. ALI also has a long-standing arrangementwith Diasonics.
GE and ALI will market UltraPACS using a team selling approach,in which GE will call in ALI sales representatives to customersites that require networking solutions. The system can also receiveimages from GE's Advantage Windows multimodality workstation,which is marketed by the vendor's network products and servicesgroup.
The agreement is appropriate for GE because it gives the vendor'sultrasound division the ability to meet customers' needs for networkingwithout draining resources from its core ultrasound business,according to Omar Ishrak, global general manager for ultrasound.
"We really want to make a difference in image qualityand the basics of ultrasound imaging," Ishrak said. "Wewant to focus on the imaging itself."
All of ALI's partnering deals are nonexclusive, giving it theoption of signing on additional OEMs. ALI will pursue this courseof action as it strives to make UltraPACS a de facto standardfor ultrasound image networking. The company's partners realizethat it is in their best interest to see the technology propagatedwidely, according to Peet.
"The key people in each organization understand that itis better for them to have more people adopting us as a solution,"he said. "The first reaction is, `I'd like to have an exclusive.
That's the wrong thing to do. We've had agreement from allof our partners who say, `Good, I'm glad there are more peoplesupporting ALI." ALI's deals could be seen as votes ofconfidence in the firm, which saw its early efforts in ultrasoundimage networking eclipsed by Acuson and its Aegis system. Sincethen, ALI has installed 25 systems, all but one of which are filmless.
Recent upgrades to UltraPACS include an image server for remoteimage transfer applications. The server is similar to a WorldWide Web page written in HTML (hypertext markup language), butis not actually on the Internet, due to patient privacy reasons.By dialing up the server over a modem or a LAN (local area network)connection, the image server can be used as an image distributionsystem in a manner similar to teleradiology. Images stored onALI's UltraPACS database can be downloaded by physicians fromany PC with a standard Web browser. The technology can also haveapplications outside ultrasound image management, according toPeet.
"We've implemented it as an extension of our system first,but we are actively promoting its use and we would love to sellit (on an OEM basis) to any other industry vendor that cares tobuy it," Peet said.
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.