{"id":4686,"date":"2025-06-03T16:05:49","date_gmt":"2025-06-03T23:05:49","guid":{"rendered":"https:\/\/unigen.com\/?p=4686"},"modified":"2026-02-12T10:17:26","modified_gmt":"2026-02-12T18:17:26","slug":"improving-the-efficiency-of-medical-image-analysis-with-ai-at-the-edge","status":"publish","type":"post","link":"https:\/\/unigen.com\/improving-the-efficiency-of-medical-image-analysis-with-ai-at-the-edge\/","title":{"rendered":"Improving the Efficiency of Medical Image Analysis with AI at the Edge"},"content":{"rendered":"
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By EOVIsion.ai<\/a>,\u00a0GenUI<\/a>, and\u00a0Unigen<\/a><\/p>\n

AI Medical image Analysis is transforming healthcare by enhancing diagnostic speed, accuracy, and cost-efficiency without replacing medical professionals. Traditional cloud-based workflows for analyzing large pathology images are often slow, expensive, and resource-intensive. A new on-premise AI inference approach leverages high-performance, low-power servers positioned directly within hospitals and diagnostic centers to dramatically reduce latency, lower costs, and strengthen data privacy. By processing ultra-high-resolution images locally and integrating an intuitive user interface, this solution enables healthcare providers to deliver faster diagnoses (often in under 30 minutes) while maintaining clinical oversight and improving patient outcomes.<\/p>\n

Advancements in medical image analysis<\/h2>\n

Medical image analysis represents one of the most revolutionary advancements in healthcare, significantly improving the diagnostic and treatment capabilities of a myriad of conditions. The field has seen rapid technological innovation over the last 100 years, from the first X-ray in 1895 to more sophisticated 3D imaging methods like CT scans and MRI technology. Today, with the advancement of Artificial Intelligence (AI), the capabilities of healthcare professionals can be enhanced (NOT REPLACED!) to improve productivity and diagnostic accuracy. We are already seeing the benefits of AI technology and we are just beginning to scratch the surface.<\/p>\n<\/div>\n

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The problem: slow and expensive medical image analysis<\/h2>\n

Every day, pathologists and researchers spend thousands of hours screening images for abnormalities or cells that could be signs of a disease such as cancer. The time of these specialists is not only a very expensive resource, but this process also creates a time latency to provide a diagnosis for the physician and the patient. The current solution to this issue requires sending large images to data centers, where the images are tiled into thousands of smaller images and then inspected by powerful servers, and the data stored in their data lakes. This process is also problematic since it involves an additional latency to transmit the data and involves extra costs for data storage and spinning up and taking down costly\u00a0GPU server<\/a>\u00a0instances in \u201cThe Cloud\u201d to perform each of the computational steps.<\/p>\n

A new approach to medical image analysis is emerging, aiming to establish the foundation for how clinical decisions are made across the healthcare industry. One such platform enables the detection and identification of anomalous cells with speed and precision, empowering healthcare institutions to improve diagnosis and deliver more focused treatments. While the platform delivers results efficiently through its secure cloud-based system, some institutions may opt to incorporate new server technology for on-premise AI inference to further reduce\u00a0latency<\/a>, strengthen data privacy, or manage long-term cloud-related costs. These options can provide additional value depending on institutional needs and operational preferences.<\/p>\n

A more efficient solution: on-premise AI inference for medical image analysis<\/h2>\n

A new solution being proposed to solve the problem of slow and expensive medical diagnostic imaging is the addition of an\u00a0inference server<\/a>\u00a0with\u00a0high performance AI Inference modules<\/a>\u00a0that are currently being adopted for high volume security camera operations which can now be\u00a0 adapted for on-premise operations in hospitals and diagnostic centers.<\/p>\n

\"Poundcake
AIC\u2019s EB202-CP Server and Unigen\u2019s Biscotti AI E1.S Module<\/figcaption><\/figure>\n

These servers, which use less than 20% of the power of a GPU server, can be co-located near the diagnostic imaging microscope to avoid the issues of transmission and costs associated with data ingress\/egress and cloud storage. This solution, which costs less than 20% of a GPU server, can significantly shorten the time for a diagnosis from hours or even days to less than 30 minutes.<\/p>\n

By reducing the latency of sending huge files over the internet, it allows a simpler path by copying them to a local server. This also affords the luxury of a large memory capacity server and an ultrafast NVMe Solid State Drive storage device, which can tile 100Kx100K pixel images into smaller 640\u00d7640 pixel frames and process them on the Inference AI modules through 32 lanes of PCIe bandwidth directly to memory, which significantly reduces the time for computation. It also can be used by a diagnostician to directly interface with the server through a VPN (Virtual Private Network) to securely view the images on the server and see if there are anomalous cells (highlighted by red Yolo squares) or an all-clear signal for a healthy image.<\/p>\n

Increasing accessibility through intuitive user interface<\/h2>\n

In addition to dramatically reducing the latency and cost of medical diagnosis, this product also makes it easy for a physician to see the result. The addition of a custom built User Interface (UI) dedicated to medical health specialists takes this from a device to a complete solution. Through the addition of a state of the art visual agent,\u00a0 this solution can provide an intuitive presentation of\u00a0 the information that allows access and navigation through the images managed for human beings.<\/p>\n

Conclusion<\/h2>\n

In conclusion, when companies with disparate technological core competencies (like\u00a0EOVIsion.ai<\/a>,\u00a0GenUI<\/a>, and\u00a0Unigen<\/a>) work together using the latest tools towards a common cause, the result can be much greater than the sum of its parts. Our goal isn\u2019t simply about building the latest and greatest technology. We are passionate about designing solutions that can impact people\u2019s everyday lives. By using our combined technology, we are not just improving the efficiency of medical diagnostic imaging. We\u2019re making sure every patient can get the timely and accurate diagnosis they deserve.<\/p>\n

Key Takeaways: On-Prem AI for Medical Image Analysis<\/h3>\n