System and method for identifying a tumor or lesion in a probabilty map

A system comprising:

• a medical imaging system;
• a processor;
• and
• a computer readable storage medium in communication with the processor, wherein the processor executes program instructions stored in the computer readable storage medium which cause the processor to:
• receive image data from the imaging system;
• generate a first and second set of two-dimensional images from the image data;
• generate a first projection image from the first set of two-dimensional images and a second projection image from the second set of two-dimensional images;
• identify a first region of interest in the first projection image;
• generate a first probability map from the first projection image and a second probability map from a second projection image, wherein the first probability map includes a second region of interest that has location that corresponds to a location of the first region of interest;
• interpolate the first probability map and the second probability map, thereby generating a probability volume, wherein the probability volume includes the second region of interest;
• and
• output a representation of the probability volume to a display.

A computer readable storage medium with computer readable program instructions that, when executed by a processor, cause the processor to:

• generate a three-dimensional volume from ultrasound data, wherein the three-dimensional volume includes a plurality of two-dimensional images;
• separate the plurality of two-dimensional images into a first set and a second set of two-dimensional images;
• generate a first projection image from the first set of two-dimensional images and a second projection image from the second set of two-dimensional images;
• identify a first region of interest in the first projection image;
• generate a first probability map from the first projection image and a second probability map from the second projection image, wherein the first probability map includes a second region of interest with a location that corresponds to a location of the first region of interest;
• generate a probability volume from the first and second probability maps;
• and
• identify a region of interest in the probability volume as a tumor or lesion.