Abstract: Image processing techniques may include a methodology for normalizing medical image and/or voxel data captured under different acquisition protocols and a methodology for suppressing selected anatomical structures from medical image and/or voxel data, which may result in improved detection and/or improved rendering of other anatomical structures. The technology presented here may be used, e.g., for improved nodule detection within computed tomography (CT) scans. While presented here in the context of nodules within the lungs, these techniques may be applicable in other contexts with little modification, for example, the detection of masses and/or microcalcifications in full field mammography or breast tomosynthesis based on the suppression of glandular structures, parenchymal and vascular structures in the breast.

Abstract: Image analysis techniques applicable to mammograms and other types of images may include image normalization, image segmentation, forming a prediction bias image, and creating an equalized image based on the prediction bias image. Creation of the equalized image may include subtraction of the prediction bias image from the original image. Forming the prediction bias image may involve the use of trained predictors.

Abstract: An image may be processed to normalize and/or remove noise from the image. The processing of the image may involve decomposition of the image into multiple components and subsequent gray scale registration across multiple scales.

Abstract: Images may be registered by performing a number of operations that may include coarse alignment, coarse registration, and fine registration. The finely-registered images may be subtracted to obtain a residual image.

Abstract: An image may be processed to normalize and/or remove noise from the image. The processing of the image may involve decomposition of the image into multiple components and subsequent gray scale registration across multiple scales.

Abstract: A user may be provided with identified regions of interest superimposed on a larger image, which may permit the user to individually examine the regions of interest. The regions of interest may be independently windowed and/or leveled and/or magnified according to parameters associated with the region of interest, which parameters may be generated by a computer-aided detection algorithm.

Abstract: Embodiments of the invention may process an input image using phase symmetry methods and use the resulting processing results to determine an object in the image. The object may be suppressed, if desired.

Abstract: Using identification of their sizes and positions, objects may be attenuated or removed from images. This may involve the use of various filtering operations and may further include coordinate transformations prior to and/or after the filtering. The filtered objects may then be subtracted from the image.