AI is revolutionizing every field it touches. The same goes for medical imaging, too. Due to the fast development of AI in recent years, the expectation is high for early detection and optimal therapy for diseases with AI’s help. Ultrasound system manufacturers, or diagnostic imaging manufacturers, in general, are investing vast amounts of money in the research of AI. The diagnostic imaging field is expected to produce significant innovations. In this article, we discuss the AI-related trends in diagnostic imaging.
Deep Learning Is Surpassing Radiologists
In 2016, an esteemed professor at the University of Toronto, professor Hinton said, “In five years, deep learning is going to do better than radiologists.” This sparked a huge debate over the world and radiologists got a huge shock as to learn that there is a real chance of AI replacing them in the near future. Technology has taken care of lots of human works. This is good because our work gets done faster than ever before but it also has a disadvantage, which is unemployment.
Radiologists are not wrong to think that their livelihood is at risk. Because startups based on AI are appearing one after another at a fast rate. DeepMind Technologies Limited is one of the most prominent ones. They started on their own but then Google bought them and now they are a part of Google. They offer support for retinal disease diagnosis. Another good example is Enlitic, Inc. who offers lung cancer detection and diagnosis support. There are hundreds of such companies across the USA only. And why shouldn’t there be? Take this for an example: DeepMind can detect diseases that lead to blindness with a 94% accuracy which is truly comparable to an actual doctor.
Incorporating AI technology in the medical field is quite easy and the cost of implementation is low. Due to these two reasons, automatic adjustment of diagnostic imaging equipment and automatic measurement will reduce the workload of the physicians and technicians. CADe or Computer-Aided Detection is developing at a quick rate with the target to support the detection of lesion candidate areas. Computer-Aided Diagnosis or CADx determines whether a lesion is benign or malignant.
In addition to these, researchers are trying to make AI capable of achieving Computer-Aided Prediction or, CAP which will make predictions using scores and probability. The most research done in the AI-related diagnostic imaging field is anomaly detection in chest and breast X-rays. Applications in lung and head examination, CT, MRI are also advancing at such a fast rate that all areas of diagnostic imaging are expected to see lots of innovations in the near future.
There are reasons why ultrasound system manufacturers or diagnostic imaging manufacturers, in general, are investing that much money in the research of AI to integrate in ultrasound medical device. The greater market share will go to the first movers. Radiologists are scared about their jobs but diagnostic imaging system manufacturers and the AI tech companies are having a good time with all the prospective innovations.