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The medical imaging industry is set to see 9 and a half billion dollars in growth in just a few years, mostly due to advances in AI imaging technologies.
AI integration with medical imaging is expected to gain traction as it enables increased productivity, improved accuracy, and reduced errors in the diagnosis performed by technicians and radiologists. The use of AI will also automate the labor-intensive manual segmentation and enable technicians to identify abnormalities, in turn, accelerating the treatment process. Furthermore, AI platforms are also being developed for hospitals and health systems to help clinicians in making quick decisions and improving patient outcomes.
Ultimately, this field of research will benefit from more minds refining the technology. This project will get you started in using Python and Tensorflow/Keras for advanced medical imaging.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
AI integration with medical imaging is expected to gain traction as it enables increased productivity, improved accuracy, and reduced errors in the diagnosis performed by technicians and radiologists. The use of AI will also automate the labor-intensive manual segmentation and enable technicians to identify abnormalities, in turn, accelerating the treatment process. Furthermore, AI platforms are also being developed for hospitals and health systems to help clinicians in making quick decisions and improving patient outcomes.
Ultimately, this field of research will benefit from more minds refining the technology. This project will get you started in using Python and Tensorflow/Keras for advanced medical imaging.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
