Posted on: 24/04/2024

AI in Radiology

Artificial intelligence (AI) is rapidly transforming the field of radiology. AI offers benefits to radiologists and patients alike.

How AI Works in Radiology

Deep learning is a powerful subset of AI in radiology and many other fields. Here's how deep learning is applied in radiology. Algorithms are trained on large amounts of medical image data. These algorithms learn to identify patterns and relationships in images. Therefore, it further helps radiologists to identify abnormalities or indicate the presence of disease with the help of macheine. AI can analyze large volumes of scans, flag those that need urgent attention, and spot even subtle abnormalities that radiologists might normally miss.

In addition to improving diagnostic procedures, AI can also improve operational efficiency by improving image quality and reducing noise and artifacts of images for better analysis. AI algorithms can analyze mammograms, X-rays and CT scans to identify suspicious lesions that may be cancerous. AI can also quickly detect and classify fractures, enabling faster treatment decisions.

Using AI will also greatly contribute to patient care. Using AI to reconstruct low-dose CT scan images into high-quality images can help reduce radiation exposure for patients.

Any how, AI is just a tool, not a replacement for Radilogists.  AI has immense potential to improve efficiency, accuracy and workflow in radiology, which will ultimately benefit patient care. Raadiance Teleradiology has already started studies to integrate the best AI applications in radiology. Raadiance is expected to introduce AI-enabled readings soon.