An ultrasonic diagnosis device sends an ultrasonic signal to an inspection target, and visualizes an internal status of the inspection target based on reflected wave information thereof. This device is used for nondestructive inspection in a medical treatment region or an industrial region.
As to the ultrasonic diagnosis device, first, by processing a signal received via a probe, two data (identical phase component data (I data) and orthogonal phase component data (Q data)) are calculated. Then, based on I data and Q data (Hereinafter, they are called “IQ data”), internal data (A-mode data, B-mode data, color Doppler data (including a direction, an averaged flow velocity, a power, a distribution), M-mode data) are calculated. By applying a coloring or a scan transform to the internal data, the inspection target is visualized as image data. Moreover, in a diagnosis using this device, the power Doppler method for visualizing power data is also used. Hereinafter, for convenience' sake, the color Doppler data and the power Doppler data are called “color Doppler data”.
Regularly, the ultrasonic diagnosis device prepares a plurality of methods for visualizing IQ data and internal data as image data. A user can select any from the plurality of methods. Furthermore, some ultrasonic diagnosis device prepares a function to preserve the image data visualized. As a result, after the diagnosis in real time, the user can confirm the image data visualized in off-line. In order to switch the plurality of methods in off-line, by preserving not the image data already visualized but the reflected wave information (IQ data, or internal data) not visualized yet, the visualization processing needs to be applied to the preserved data again.
However, a data quantity of the reflected wave information is much larger than that of the image data visualized. Accordingly, preservation of all reflected wave information unprocessed is not realistic. Furthermore, if compression processing is applied to all reflected wave information inputted, processing quantity is enormous. As a result, processing time thereof becomes very long.