Hassan Rivaz: Machine Learning in Medical Ultrasound скачать в хорошем качестве

Hassan Rivaz: Machine Learning in Medical Ultrasound

This talk focuses on developing image analysis techniques that reveal otherwise hidden information in clinical ultrasound signals. Ultrasound is one of the most commonly used imaging modalities because of its low cost and ease of use. However, it has two main drawbacks. First, raw ultrasound data is not suitable for visualization, and as such, is converted to the familiar grey-scale images which leads to a loss of most of its information. Second, these grey-scale images are hard to interpret since they are noisy and collected at oblique angles. In this talk, we tackle these issues by developing techniques that extract clinically useful information such as tissue elasticity from the complex raw ultrasound signals, and register them to other modalities such as Magnetic Resonance Imaging (MRI) to help with their interpretation.