One of the most exciting developments in the field of orthopedic surgery has been the integration of artificial intelligence (AI) into medical imaging. Two notable AI-driven solutions have emerged as contributors to this step into AI, Axial3D’s INSIGHT and ImageBiopsy Lab’s IB Lab Squirrel.
INSIGHT’s primary function is to automate the conversion of 2D Digital Imaging and Communications in Medicine (DICOM) images into precise 3D visualizations. This conversion process grants orthopedic surgeons more detail and accuracy when assessing patients’ injuries. The platform essentially translates complex 2D scans into vivid 3D models, providing surgeons with a newfound clarity.
On another front, ImageBiopsy Lab’s IB Lab Squirrel focuses on AI-powered assessments of scoliosis-related indications affecting the spine. Scoliosis is a condition that poses diagnostic and tracking challenges. However, IB Lab Squirrel employs AI to deliver remarkably accurate assessments.
The advantage these AI-driven solutions offer lies in their ability to save valuable time and enhance diagnostic accuracy. In the fast-paced field of orthopedic surgery, every moment counts. Rather than spending precious minutes to decipher 2D images or manually measure angles, surgeons can entrust AI to handle these tasks efficiently and with precision.
Furthermore, AI can be used to analyze CT scans. These scans provide invaluable insights, yet their complexity can b e overwhelming. AI algorithms can view these images, identify minuscule details, spot potential issues, and even predict outcomes with accuracy. Additionally, AI can take the same data sets and interpret it in multiple ways. For example, while radiologists might be looking for signs of cancer in the CT scan, AI can take the same CT scan and extrapolate data about body composition.
Nonetheless, it is important to recognize that AI remains a tool, subject to the quality of its training data and human supervision. Surgeons remain indispensable in interpreting AI-generated results and employing their expertise to make well-informed decisions.
In the dynamic landscape of orthopedic trauma surgery, AI continues to shape the future of patient care. Beyond the specific applications mentioned, AI also contributes to many other aspects of an orthopedic surgeon’s work, such as streamlining workflow and aiding in surgical planning. As AI algorithms evolve and integrate more into the orthopedic surgical toolkit, they empower surgeons to make data-driven decisions, reduce the margin of error, and ultimately offer patients a higher standard of care.
