Abstract: A method and an apparatus for improving the contrast of the displayed image data in a B-mode ultrasound imaging system. An adaptive gray mapping is based on the actual raw imaging data instead of assumptions about that raw data. The user specifies a region of the image (or the entire image) with a graphical region-of-interest (ROI) marker. When prompted by the user, a software program in the master controller analyzes the raw data within the ROI and constructs a new gray map based upon the analyzed data. This mapping can be created by transforming an old gray map or by generating a new gray map. This new gray map is then used by the ultrasound system during imaging. Optimum contrast is achieved by automatically adjusting the brightness and contrast levels of the image based on the values of the raw data.

Abstract: A method and an apparatus for automatically adjusting the contrast of a projected ultrasound image. An ultrasound scanner collects B-mode images in a cine memory, i.e., for a multiplicity of slices. The data from a respective region of interest for each slice is sent to a master controller, such data forming a volume of interest. The master controller performs an algorithm that iteratively projects the pixel intensity data in the volume of interest onto a plurality of rotated image planes using a ray-casting technique. Before the projected images are stored in cine memory, the contrast of the pixel intensity data making up those projected images is adjusted by the master controller using a one-to-one mapping of unadjusted pixel intensity data into adjusted pixel intensity data. The mapping is generated by the master controller based on the pixel intensity data of either a source frame or a projected image. The contrast adjustment mapping is applied to each projected image.