Deep Learning – The Future of Medical Imaging

The future concerning radiology and deep learning comes with varying emotions and reactions.

For starters, there are many who are concerned about the disruptions that might come to radiology. Many fear that the advanced technology will take away their jobs. Others believe that the advancements will just expand radiologist roles in predicting disease and guiding treatment.

Signify Research released a report stating that deep learning will be a $300 million market by 2021. Deep learning will continue to advance, addressing many industry challenges as it does so.

According to principal analyst Simon Harris, “Radiology is evolving from a largely descriptive field to a more quantitative discipline. Intelligent software tools that combine quantitative imaging and clinical workflow features will not only enhance radiologist productivity, but also improve diagnostic accuracy.”

Signify outlines four layers of image analysis software:

  1. Computer-aided detection

  2. Quantitative imaging

  3. Decision support tools

  4. Computer-aided diagnosis

Computer-aided detection is the most common and the most readily available due to its relatively easy implementation.

Although the list contains several items, there are still many hurdles to get over. With so few available solutions, the evidence just isn’t there to prove that the technologies can deal with variations in patient demographics, protocols, and image artifacts. Nevertheless, Signify says deep learning should not be underestimated; it is a question of when, not if, machine learning will become a permanent presence in the medical imaging world.

Machine learning uses algorithms to build analytical models, meaning the computers “learn” from the data. Intelligent software tools that combine quantitative imaging with clinical workflow features will, as mentioned, enhance radiologist productivity and improve accuracy.

Some may want to dig their heels in, afraid that these advancements will put their job at risk. However, it is staying abreast of these advancements, being knowledgeable, and being one of the first to implement them that will keep you on the cutting edge and an asset to the field.

#imaging #CAD #robots #artificialintelligence #computeraideddiagnosis #computeraideddetection #deeplearning #radiology #machinelearning #medicalimaging

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