Wingspan Launches Global Imaging Cloud Service Solution, Upgrading Its Medical Imaging Ecosystem
On November 14, 2019, the 26th National Academic Congress of Radiology (CCR 2019) of the Chinese Medical Association was officially held in Beijing. Wingspan Medical Group made a stunning appearance with multiple latest products and grandly launched its “Global Imaging Cloud Service Solution” during the exhibition, unveiling five major themes on site.
Medical imaging data accounts for 80% of all healthcare data. Currently, a single patient’s CT scan can easily reach hundreds of megabytes in size, while state-of-the-art thin-slice CT scans can generate up to 1 GB of data per case. Transmitting such large imaging files even over hospital wired networks results in significant latency. By leveraging 5G technology, rapid transmission and real-time analysis of massive imaging datasets become possible, ushering in unprecedented opportunities for regional collaborative image diagnosis and AI-driven medical imaging.
The highlight of this Wingspan launch event was the new-generation Wingspan AI+5G Box (3.0). As an edge computing intelligent gateway equipped with a 5G communication module, it enables the transmission of data from numerous medical imaging devices across different on-site areas to the cloud, while providing real-time quality control, remote monitoring, remote maintenance, and fault warning capabilities. This provides a solid foundation for building large-scale remote medical imaging diagnostic platforms. In the 5G era, experienced experts can provide remote image interpretation, operational guidance, and even diagnoses to primary care hospitals in just moments, thereby more effectively supporting tiered diagnosis and treatment and enabling people in remote areas to access high-quality medical services more conveniently and efficiently.
Edge computing entails bringing cloud computing resources, computational power, and storage capabilities closer to users on local edge devices, enabling independent local processing of large volumes of data and decision-making. In the field of “AI + Medical Imaging,” deploying AI models at the edge can significantly reduce data communication costs. By processing data locally, it avoids the challenges associated with storing massive amounts of data in the cloud. With the explosive growth of connected devices and increasing demands for privacy/confidentiality and low latency, integrating machine learning intelligence into edge computing devices allows us to shed historical burdens and pave the way for new scenarios and business opportunities.
Image acquisition quality directly impacts diagnostic interpretation. Due to scarce medical resources and insufficient technician experience in township health centers, the quality of acquired images cannot be guaranteed, causing significant difficulties for senior radiologists during remote diagnosis. To address this issue at its root and improve the overall imaging proficiency of grassroots technicians, Wingspan has deployed an AI-based image quality control application on edge computing devices—the new-generation Wingspan AI+5G Box. After grassroots facilities transmit acquired images to the Wingspan Box, the AI system evaluates image quality. If the image is classified as non-Grade A, the technician is immediately prompted to retake the image. Compared with scenarios lacking edge computing, where images are already transmitted to and processed in the cloud before radiologists identify substandard quality and request a rescan, the feedback loop in the Wingspan AI Box edge computing scenario is significantly more timely. This reduces time costs associated with communication and repeated data transmission, thereby accelerating the entire remote imaging diagnostic process.
In 2013, Wingspan pioneered the launch of China’s first internet-based medical imaging diagnosis platform, “Cloud Imaging.” By leveraging a model integrating “data + cloud technology + clinical scenarios,” it has built a comprehensive solution encompassing remote diagnosis, remote consultation, remote education, and telemedicine operations. This approach utilizes internet technologies to allocate high-quality diagnostic resources across regions, addressing the shortages in both the number and experience of radiology staff at primary care hospitals, thereby enhancing the accessibility of grassroots medical services.
As a leading enterprise in the medical imaging industry, Wingspan is committed to innovation, continuously refining its products and pushing boundaries. At this launch event, it proudly unveiled the world’s first remote imaging diagnosis platform integrating nuclear medicine and ultrasound, as well as a regional intelligent cloud imaging platform based on blockchain technology. These solutions enable patient-centric access control and usage management of imaging data through more secure, tamper-proof, and privacy-preserving data storage methods.
Currently, Wingspan's "Cloud Shadow" features:
Comprehensive cloud-based 3D reconstruction capabilities, supporting 3D MPR, MIP, MinIP, and AIP, with convenient adjustment of slice thickness and rotation at arbitrary angles, providing radiologists with a superior remote image interpretation environment;
The 3D fusion capability of PET-CT displays fused PET-CT images in MPR and MIP 3D views, facilitating the observation of tissue changes and precise lesion localization by physicians. Additionally, three new pseudo-color schemes are introduced to provide more options for clinicians.
Remote Ultrasound Consultation Function: Leveraging cloud-based audio-video conferencing systems, intelligent camera hardware, and the Wingspan Cloud Imaging Diagnostic Platform to enable remote ultrasound consultations. This solution facilitates communication between different offices or campuses within a hospital, as well as supporting remote ultrasound solutions under the regional medical internet model.
Certainly, the capabilities of Wingspan’s “Cloud Shadow” extend beyond this; the platform currently also supports online viewing, manipulation, and diagnosis of imaging studies such as CT angiography (CTA), mammography, fundus images, and endoscopy.
Wingspan “CloudShadow” Blockchain envisions leveraging blockchain technology to build a secure, transparent, and efficient network for sharing medical imaging data. By maximizing the protection of patient privacy and data security, it aims to accelerate the circulation and exchange of medical imaging data, enhance the efficiency of remote diagnosis in medical imaging, ensure the immutability and traceability of imaging reports, and facilitate the collection and annotation of training data for medical imaging AI. Furthermore, it seeks to expand the application of distributed medical imaging AI, thereby benefiting patients, radiologists, hospitals, third-party imaging centers, and medical imaging AI vendors alike.
At this press conference, Wingspan officially unveiled its AIDiscovery AI-powered open collaboration platform for medical imaging alongside leading radiology experts, and simultaneously launched version 2.0 of the Wingspan Rogen Ruiyi DR Chest X-ray Automated Reporting System.
AIDiscovery is an end-to-end open AI collaboration platform that rapidly builds, deploys, and launches state-of-the-art medical imaging AI applications using a standardized model. Functioning as the “App Store” of the medical imaging world, the AIDiscovery platform provides AI companies and developer teams worldwide with the most convenient means to host applications and commercialize their products, thereby fostering a healthcare industry ecosystem, optimizing the medical imaging diagnostic workflow, extending coverage to more healthcare institutions, and assisting physicians in making better clinical judgments. Wingspan aims to build increasingly comprehensive, scalable, and capable systems and platforms through every integration, partnership, and iteration, empowering healthcare institutions and radiologists to ensure that all patients have equitable access to high-quality diagnostic results.
Currently, the applications that have been partnered with or launched on AIDiscovery include an automated diagnostic report system for computer-generated DR chest X-rays, thermal imaging recognition for pulmonary diseases, automatic annotation and analysis of CT lung nodules, an intelligent text error-correction assistant, real-time quality control for chest X-rays, diagnostic assessment of arterial plaques in MRI, and automatic detection of cerebral hemorrhage in brain CT scans.
Notably, at last year’s CCR conference, Wingspan unveiled its independently developed Wingspan Rogen Ruiyi DR Chest X-ray Automated Reporting System, and this year it has launched version 2.0 with a completely new core. The updated automated reporting system employs an advanced deep learning model, incorporating nearly 100,000 additional DR chest X-ray images and their corresponding reports as training data. It expands disease recognition from the original 17 conditions to include rib fractures, significantly enhancing overall model performance. The entire diagnostic report generation process now takes only 0.8 seconds. Compared with physicians’ reports, AI-generated reports matched or exceeded physician performance in over 75% of cases across key metrics, including “overall performance, report readability, ability to identify critical information in images, ability to describe lesions and abnormal regions, ability to count lesions, and ability to describe abnormal findings.”
The launch of Wingspan’s “Globalized Imaging Cloud Service Solution” not only signifies that the products and services within its medical imaging cloud-enabled ecosystem are better equipped for global expansion, but also marks Wingspan’s comprehensive acceleration of its business-level globalization strategy. Following the signing of the “Strategic Framework Agreement on Technology Service Export and ‘Internet + Healthcare’ Demonstration” with the Ningxia Health Commission and the China-ASEAN Economic and Trade Promotion Association this September, Wingspan has further established closer healthcare cooperation mechanisms with countries along the Belt and Road Initiative and in Southeast Asia. By exporting China’s advanced medical capabilities globally, Wingspan aims to ensure people worldwide have access to high-quality healthcare services, promote the building of a global community of shared health through enhanced connectivity, and contribute significant Chinese strength to the development of global healthcare.