Abstract: A method for providing an enhanced 3-D image for a volume imaging apparatus obtains 3-D volume images of an object at a first resolution and forms a 3-D matrix of voxels at a second, higher resolution. Two or more 3-D volume images that have different spatial orientations and that intersect at the voxel are registered. The voxel is mapped to the 3-D matrix. Inpainting fills in gap regions between mapped voxels in the 3-D matrix. A simulated first-resolution data value is generated according to one or more 3-D matrix values. The simulated first-resolution data value is compared with an observed first-resolution value from the 3-D volume images and, until the simulated first resolution data value is within a predetermined threshold value of the observed first-resolution value or until a predetermined number of iterations is reached, the 3-D matrix voxel values are adjusted and the simulated first-resolution data value recomputed.

Abstract: A method for providing an enhanced 3-D image for a volume imaging apparatus obtains 3-D volume images of an object at a first resolution and forms a 3-D matrix of voxels at a second, higher resolution. Two or more 3-D volume images that have different spatial orientations and that intersect at the voxel are registered. The voxel is mapped to the 3-D matrix. Inpainting fills in gap regions between mapped voxels in the 3-D matrix. A simulated first-resolution data value is generated according to one or more 3-D matrix values. The simulated first-resolution data value is compared with an observed first-resolution value from the 3-D volume images and, until the simulated first resolution data value is within a predetermined threshold value of the observed first-resolution value or until a predetermined number of iterations is reached, the 3-D matrix voxel values are adjusted and the simulated first-resolution data value recomputed.

Abstract: A method of determining the skin-line in a digital medical image comprising the steps of:providing a digital medical image including a matrix of lines and columns of pixels;determining the minimum gray level of the background pixels using a background detection routine;selecting all or at least a representative sample of said lines and/or columns of said image, and for each selected line or column;smoothing the line to minimize the effect of noise on the delineation of pixel gray level transitions;identifying significant transitions from segments of monotonically decreasing gray level values that span a minimum gray level range and start near or above said minimum background gray level;computing a set of features for each identified significant transition; andbased on the set of features computed for each of the identified significant transitions, classifying the transition as either a skin-line transition or as a non-skin-line transition.

Abstract: A method of identifying tissue regions in a digital image representing a body part provides a digital image representing a body part having tissue regions. The digital image is scaled by subsampling or interpolation, and texture extraction is applied to the scaled image to produce a plurality of texture images each having a different measure of the image texture. The texture images are clustered, and the clustered image is labeled based on both pixel intensity values and geometric adjacency of pixels. A threshold is applied to the labeled image, which is then filtered using a largest component filter system to determine the largest geometrically connected region in the threshold image. The filtered image is subjected to edge detection to produce an edge image containing only edge pixels at high code value, and the edge image is operated on to produce a convex hull image which outlines the skin line of the tissue region of the body part provided in the digital image.