Using the Sonification for Hardly Detectable Details in Medical Images

In this paper, the inverse sonification problem is analysed in order to capture hardly detectable details in a medical image. The direct sonification problem is converting the data points into audio specimens by a transformation which involves data, acoustics parameters and sound representations. The inverse problem is reversing back the audio specimens into data points. By using the current sonification operator, the inverse approach does not bring any improvement in the medical picture after sonification. The obtained image is the same with the original one and does not bring additional information for diagnosis and surgical operation. In order to discover new details in a medical image, a new operator is introduced in this paper, by using the Burgers equation of sound propagation. The improving of the medical image is useful in interpreting the medical details in the tumour surgery. The inverse approach is exercised on several medical images.

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