LifeVoxel.AI Interactive Streaming & AI Cloud Platform
LifeVoxel.AI enables interactive cloud visualization over Internet while maintaining image diagnostic
HD quality without transmitting raw scan.
The field of medical imaging today faces a number of challenges. The most important of these is a dearth of radiologists in many locations and associated lag in turnaround time. Both these problems can be rectified via the deployment of powerful technology alternatives.
Medical image visualization over the internet is the way forward and it can bring about an improvement in outcomes. However, maintaining the quality of images to meet the diagnostic standards is a challenge. Another issue that needs to be addressed is the speed and accessibility. When it comes to medical images the time gap for transmission is also critical as is the minimizing of human error with regard to reading the images. The incorporation of Artificial Intelligence can help improve turnaround time as well as reduce the incidence of human error. But present ICT solutions that are being deployed in other domains cannot cater to the field of medical imaging. This is due to the nature of the files that are being transmitted as well as the field-specific requirements. For example, the top-rated content delivery networks today have a latency of 0.5 to 3 seconds, which is far from the desired latency that is expected in medical image transmission. Credible evidence states that latency is the most significant issue faced by more than half (54%) of video developers in the industry. Furthermore, conventional RIS, PACS, Enterprise Imaging (VNA and Image Sharing) are unsuitable for AI and 3D/VR/AR. A large amount of investment is needed to develop and improve upon the available technology in medical imaging.
When it comes to the consumer side, the issue of cost is a major factor. Often many consumers settle for lower grade options due to a misconstrued notion that the best technology is unaffordable for them. The problem of compatibility across devices and platforms also needs to be addressed.
The AI Revolution
Artificial Intelligence(AI) is widely regarded as the technology for the future. It offers immense scope in the field of medical imaging as well. Machine Learning and related AI concepts can help reduce the turnaround time of medical images. Time is a crucial factor in this domain and AI has the potential to drastically reduce time lags and thereby save lives. This technology can help reduce the incidence of human error as well. With AI powerful algorithms are executed to find patterns and help read medical images.
The possibilities on the Cloud
RIS PACS servers once helped bring down space and cost needs for medical data storage. But today they have been seen to be inefficient in scaling up to the required needs. Going on the cloud helps in easing the transfer of medical images as well as improving their storage. It can correct the mismatch in workload and availability of radiologists in specific locations by making it possible for radiologists from far off locations to access such work effortlessly. But there are certain complications when it comes to going on the cloud. Medical images are not like any other piece of data that you put on the cloud. Latency sensitivity, compatibility and image quality are some of the main concerns here. Traditional could majors may not be adequate in handling these issues and taking medical images to the cloud. Specific technology needs to be developed to ensure that the medical imaging industry makes the best out of the cloud.
GPU Computing for Latency and Efficiency
GPU Computing is a powerful piece of technology and can process information at a rare of 3000x more than conventional CPU computing. GPUs are considered as the heart of AI and can be put to great use in improving the quality and latency sensitivity in medical imaging. Another important thing to note is that GPUs occupy a very small amount of space unlike the monstrous hardware space taken by CPUs if they are required to perform highly powerful functions. GPUs can also help take medical images to the cloud efficiently.
Streams visualization real-time using patented server-side technology. LifeVoxel.AI provide instant access to time critical stroke patient images to remote physicians and patients in 3D
LifeVoxel.AI’s real-time streaming visualization makes use of patented server-side technology. Server-side Rendering leads to the creation of beautiful content which can improve outcomes. Using this instant access to time-critical stroke patient images can be made available to remote physicians and patients in 3D (FDA 510K cleared primary diagnostic use). Universal diagnostic viewing has also been achieved which addresses the issue of compatibility.
High-end technology such as AI, GPUs and cloud computing can rectify the problems faced in the domain of medical imaging. More investment towards enhancing the application of these technologies need to be made if we are to improve the accessibility and ensure that quality healthcare reaches every doorstep. Experience our new technology & witness the speed, ease of workflow, unique capabilities and let us explain you the cost saving benefits.