Utilizing Imaging Technology in Pharma Industry
- MAKING THE MOST OF IMAGE ANALYTICS
The emergence of AI technologies such as data mining has provided healthcare organizations with new and effective tools to manage medical images. Medical imaging has changed the landscape of medicine, equipping healthcare providers with robust and practical tools to augment their services. The primary functions of conventional imaging devices once ranged from storage to retrieval. However, the emergence of revolutionary imaging systems such as picture archiving and communication system (PACS) and vendor neutral archive (VNA) have transformed medical technology.
The latest technologies leverage artificial intelligence (AI) to deliver advanced analytics to aid in healthcare operations. Although most imaging systems utilize the Digital Imaging and Communications (DICOM) standard, the adoption of PACS and VNA will require comprehensive infrastructure and the collaboration of various departments regardless of the product.
The PACS and VNA platforms have the capabilities of image storage, export and routing, quick access to images from multiple viewing stations, accommodation of DICOM standards, report generation, user templates, and HL7 support. The growing competition in the market has spurred various organizations to integrate AI capabilities to their imaging platforms.
The AI-powered imaging platforms leverage machine learning, algorithms, and image processing to analyze the trove of images and draw actionable insights. It allows the systems to maintain a high level of accuracy during the operations.
For instance, image-based diagnosis of diabetic retinopathy utilizes AI technology to analyze images of the eye and determine the condition. The procedure is carried out through an IDx-DR device and takes no more than a few minutes. The system provides the test results approximately 20 seconds after capturing the image.
The emergence of AI medical imaging devices has enabled healthcare organizations to enhance patient care and improve productivity. The significant capabilities include abnormality detection through machine learning and image processing, smart dictation via natural language processing, health data mining, image processing and analysis, and high-risk patient detection.
The effective implementation of PACS and VNAs require comprehensive planning, not only in infrastructure but also on the end-user fronts. The robust AI systems will need flexible IT environments, along with storage, processing power, and integration support. Also, many of the imaging systems in the market are at a nascent stage and need further upgrading. However, the technology is evolving, and it will not be long before every healthcare organization adopts AI imaging platforms to enhance their services.
2. THE LEAP OF MEDICAL IMAGING TECHNOLOGY
The Pharma industry has seen a vortex of changes in recent years from new policies to legislation to advanced use cases and innovations in technology. The diagnostic imaging technology sector witnesses several trends more toward patient-centric radiology and value-based imaging. Continuing research and development in medical imaging improves clinical analysis changing the landscape of modern medicine. Some of the new trends in medical imaging include:
Computed Tomography (CT): CT scan is the workforce of advanced medical imaging. They enable better management of patient care including high-quality image, dose guidance and regulation, and expansion of cardiac and brain imaging. Technology in CT has evolved from a single slice scanner to ultra-fast multidetector CT scanners reducing the acquisition time, increasing the spatial resolution along with modifications to reduce patient radiation dose. The potential of dual-energy CT is also an exciting development that offers great promise.
Tomosynthesis or 3D mammography: It allows three-dimensional (3D) reconstruction of the breast tissue, which can then be viewed as sequential slices through the breast. This new technique reduces error and allows a thorough examination of even dense tissue and facilitates detection of tiny lung nodules and chest pathologies that can go undetected with conventional methods.
Magnetic Resonance Imaging (MRI): MRI’s applications are widely used for assessment of hepatic stiffness and the stage of fibrosis in patients with liver disease. It can assist as a safer, less expensive, and accurate alternative to an invasive liver biopsy which is currently the standard for diagnosis and staging of liver fibrosis.
Cloud Technology: It enables electronic medical records to be placed on Cloud platforms to seamlessly share information with healthcare providers for completely integrated patient care.
3D Printing and Computer-Aided Design: 3D-printing technique allows clinicians to produce highly detailed models of human anatomy for better planning of complex surgical cases using the data acquired from CT images.
Exciting trends in medical imaging will continue to impact the medical landscape as mobile applications, IoT, analytics, big data, and other innovations continue to unfold.
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