System and method for segmentation and visualization of medical image data

A computing device comprising:

• a processor;
• a display coupled to the processor;
• a user interface coupled to the processor for entering data into the computing device;
• and
• a memory coupled to the processor, the memory storing program instructions that when executed by the processor, causes the processor to:
• load a plurality of two-dimensional MRI image data, the two-dimensional MRI image data taken along multiple planes to create a stack of two-dimension MRI images;
• load a three-dimensional anatomical model associated with an anatomical area of the two-dimensional MRI image data;
• segment the three-dimensional model may into multiple components, at least one of the components being modified to accurately represent the slacked two-dimensional images to form a modified three-dimensional model;
• adjust at least one property on the modified three-dimensional model to form a modified anatomical model to match the medical data image;
• detect if areas on the modified three-dimensional anatomical model exceeds predefined ranges indicating potential injured areas;
• and
• form one of an automated video or animation creation of the modified anatomical model.

A computing device comprising:

• a processor;
• a display coupled to the processor;
• a user interface coupled to the processor for entering data into the computing device;
• and
• a memory coupled to the processor, the memory storing program instructions that when executed by the processor, causes the processor to:
• load a plurality of two-dimensional MRI image data, the two-dimensional MRI image data taken along multiple planes to create a stack of two-dimension MRI images;
• load a three-dimensional anatomical model associated with an anatomical area of the two-dimensional MRI image data;
• segment the three-dimensional model may into multiple components, at least one of the components being modified to accurately represent the stacked two-dimensional images to form a modified three-dimensional model;
• generate, using machine learning trained by previous segmented three-dimensional models, an MRI report, wherein generate using machine learning trained by previous segmented three-dimensional models, an MRI report comprises:
• segment each component;
• detect and grade abnormalities in each component;
• and
• compile a summary of the detected and graded abnormalities;
• adjust at least one property on the modified three-dimensional model to form a modified anatomical model to match the medical data image:
• detect if areas on the modified three-dimensional anatomical model exceeds predefined ranges indicating potential injured areas;
• store the modified anatomical model in the database as a new anatomical model;
• and
• form one of an automated video or animation creation of the modified anatomical model.