Imaging makes up a significant amount of healthcare content, from X-rays and CT-scans to MRIs and PET scans. Within each image hides key insights into a patient’s health and associated metadata about age, gender and patient demographics. This data can influence diagnoses from healthcare providers, rare disease research, clinical trial design and much more.

While rich in insight, managing and analyzing medical images is incredibly complex. Images come in a variety of modalities, are produced by different departments such as radiology and pathology, and are utilized differently across the healthcare organization – from radiologists and pathologists to researchers and analysts.

In addition, image files are much larger than traditional data sources – making them difficult to share while taking up valuable storage.

Streamlining Medical Imaging Analysis

These factors lead to healthcare organizations spending significant time and financial resources on imaging – from tasking highly-skilled professionals with tedious image analysis to assigning IT to manage and provision infrastructure needed to utilize these assets.

Advancements in deep learning are changing the way healthcare organizations approach image analytics practices by enabling users to: 

  • Unify and catalog image assets across the organization. 
  • Enhance image detection and classification. 
  • Make images easily searchable via simple annotation. 
  • Improve image model training and management. 

Retina, Vyasa’s image analytics solution, provides pre-built deep learning models to help users integrate and manage their image assets across an organization. Analytical modules built into Retina can perform a wide range of image analytics tasks, such as helping to detect breast cancer in mammography screening images

With a streamlined approach to image analytics, healthcare professionals can easily filter their image libraries to include just their most relevant content, quickly identify cohorts for clinical trials, improve research accuracy for pathology and radiology reports, and much more. 

Users use Vyasa Retina to enhance their image analytics through intuitive annotations and tagging.

Optimized Performance with NVIDIA Solutions

Through our collaboration with NVIDIA, users can optimize Vyasa with the NVIDIA AI Enterprise software suite for accelerated deployment of AI applications within their environment. Vyasa also leverages the NVIDIA Clara application framework for accelerated imaging workflows that enable enhanced analytics across large data sets.

Unlocked Image Insights for Healthier Populations

As a critical source of insight, the ability to easily unlock the data within images holds tremendous promise for healthcare. By deploying deep learning image analytics, healthcare organizations will find more productive medical providers and a happier IT team, but most importantly a healthier population thanks to enhanced early detection and accelerated time to diagnosis. 

Interested in learning more about how Vyasa is enhancing the analysis of medical imaging? Visit us at Dell Technologies booth #2000 at HIMSS 2022