Patent ID: 9538920
Date: 2017-01-10
CPC Classifications: A61B,G06K,G06T

Claim:
1. A computer-implemented method to create annotations of spine images, the method comprising: loading reference data comprising prior geometric measurements of the human spine; receiving an initial input from the selection of a point within a vertebral region in a single, two-dimensional axial-view image slice of a spinal magnetic resonance image series; generating a target distribution of identified pixel intensity values for said vertebral region; classifying each of a plurality of pixel intensity values of each said image slice of said spinal image series to determine whether such pixel intensity value belongs to vertebrae by matching each pixel context to said target distribution using a non-linear probability product integral kernel; wherein the context of the pixel is the kernel density estimate of intensities within a window centered at the pixel; classifying each of said image slices of said spinal image series by computing a two-dimensional slice-level feature which is derived from the classification of said plurality of pixels of said spinal image series and from said reference data; identifying three-dimensional vertebra from said two-dimensional image slice-level features; and generating an annotation to at least one of said two-dimensional axial image slices identifying at least one vertebra or an associated intervertebral disk.