AI System to Generates Synthetic Scans of Brain

These scans are used to teach AI diagnostic system
18 September 2018   1110

A group of researchers developed an artificial intelligence capable of generating sets of images of an MRI of a human brain. The technology is designed to increase the effectiveness of training AI, specializing in the diagnosis of brain cancer. Tests showed that the effectiveness of diagnostic programs trained on generated kits increased by 14%.

The project was implemented jointly by specialists from NVIDIA, the Mayo Clinic and the Clinical Data Research Center. Development based on the generative and adversarial network structure (GAN) was conducted on the NVIDIA DGX platform using the PyTorch deep training systems. Two interconnected artificial intellects were used. One network generated its own MRI snapshots on the basis of real ones, and the second tried to distinguish real from fake ones.

GAN automatically marks the created sets of MRI images, which significantly speeds up learning. With manual annotation, this work takes experts many hours. In addition, since the system does not consider the brain and tumor as a whole, the operator can correct the picture by moving the tumor or changing its size.

Hu Chang, one of the authors of the study, said that the generated MRI kits also solve the problem of using confidential information. These pictures form a medical secret, and permission is required to use them. And the resulting system can be publicly available.

Hardware limitations forced the team to reduce the resolution of the original images by 8 times. Also, at the moment, neoplasms sometimes look "superimposed" on a snapshot. In the future, researchers plan to eliminate these shortcomings.

When teaching neural networks-diagnosticians, the question of the availability of training datasets is relevant. Developed by German scientists, AI, which determines myocardial infarction by ECG, used as input only 200 records. According to the creators, this seriously worsened the efficiency of the system. Tools that create datasets for learning neural networks are designed to help solve this problem.

AI to Recognize Text Written by Invisible Keyboard

Developers said they tried to increase the typing speed on the on-screen keyboards
06 August 2019   152

Korean developers have created an algorithm that recognizes text printed on an imaginary keyboard on a touchscreen. Such a “keyboard” is not tied to a specific area on the screen, and the “keys” are not limited to clear squares.

As a result, a person types blindly in a QWERTY layout without thinking about where the keyboard should be and whether it got into the key.

Imaginary Buttons Press CloudsImaginary Buttons Press Clouds

According to the developers, they tried to increase the typing speed on the on-screen keyboards. The on-screen keyboard, unlike the hardware keyboard, does not offer feedback that confirms pressing. There is a risk to miss and not press the desired button. Because of this, people endlessly stare at the screen and eventually print more slowly.

The new algorithm allows you not to worry about this, you can enter text from memory, and the keyboard with 96% accuracy will guess what the person wanted to say. Tests have shown that the average typing speed on an imaginary keyboard is slightly less than on a hardware keyboard: 45 words per minute versus 51.