Abstract: The present invention is a set of algorithms or calculations that may be applied to efficiently use atlas-based segmentation using QBinary (binary and/or quasi-binary) representations of images and/or their ROIs. A QBinary representation of an image or a part of an image (for example, such as a ROD may be a binary image (for example, such as a code with 1 bit) and or a quasi-binary image (for example, such as a code with more than 1 and less than 8 bits) that serves to represent that image and/or ROI in an atlas. Two-dimensional QBinary codes may be used to both construct QBinary atlases and QBinary-controlled atlases with or without QB-Codes registration. Additionally, the present invention may offer a set of algorithms to sequentially auto-contour (or auto-segment) individual slices of a volume set of digital images without or without QB-Codes registration, provided one slice is semi-automatically contoured by a human operator.

Abstract: The present invention provides a system, method and computer program providing automated window memoization which is an automated optimization of image processing. The method comprises inputting to a memoization compiler an image set, hardware or software code implementing one or more image processing algorithms, and one or more design parameters. The memoization compiler processes the image set for the image processing algorithms and implements hardware or software code for optimizing the image processing algorithms based on the design parameters.

Abstract: A system and method are disclosed to provide a solution to automatically generate consensual and consistent segmentation results to reduce the effects of inter- and intra-observer variability in contouring medical images, respectively. The invention may be used by multiple users with access to an internal or external network or via cloud-computing devices but it does not require having instant access to multiple users for generating the consensus or consistent contours. The invention is applicable on a multitude of medical image modalities such as CT, MRI, Ultrasound, PET and fused images.

Abstract: The present invention is a set of algorithms or calculations that may be applied to efficiently use atlas-based segmentation using QBinary (binary and/or quasi-binary) representations of images and/or their ROIs. A QBinary representation of an image or a part of an image (for example, such as a ROD may be a binary image (for example, such as a code with 1 bit) and or a quasi-binary image (for example, such as a code with more than 1 and less than 8 bits) that serves to represent that image and/or ROI in an atlas. Two-dimensional QBinary codes may be used to both construct QBinary atlases and QBinary-controlled atlases with or without QB-Codes registration. Additionally, the present invention may offer a set of algorithms to sequentially auto-contour (or auto-segment) individual slices of a volume set of digital images without or without QB-Codes registration, provided one slice is semi-automatically contoured by a human operator.

Abstract: The present invention provides a system, method and computer program providing automated window memoization which is an automated optimization of image processing. The method comprises inputting to a memoization compiler an image set, hardware or software code implementing one or more image processing algorithms, and one or more design parameters. The memoization compiler processes the image set for the image processing algorithms and implements hardware or software code for optimizing the image processing algorithms based on the design parameters.