# Leo Grady, Yardley US

## Leo Grady, Yardley, PA US

Patent application number | Description | Published |
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20080226169 | ACCELERATED IMAGE VOLUME SEGMENTATION USING MINIMAL SURFACES GIVEN A BOUNDARY - A method for image volume segmentation includes receiving an input image, obtaining an oriented closed contour on one or more slices of the input image, determining a minimum-weight surface from the oriented closed contour using a minimum-cost circulation network flow, and outputting the minimum-weight surface as a segmentation of the input image. | 09-18-2008 |

20080260247 | INTERACTIVE IMAGE SEGMENTATION BY PRECOMPUTATION - A method for interactive image segmentation includes receiving an image to be segmented, performing an offline computation of eigenvectors of a Laplacian of the image without using seed points, receiving seed points, and performing an online segmentation taking the seed points and the eigenvectors of the Laplacian as input and outputting a partition of the image. | 10-23-2008 |

20080310716 | EDITING OF PRE-SEGMENTED IMAGES USING SEEDS DERIVED FROM CONTOURS - A method for processing an object in image data includes the steps of drawing a contour on a pre-segmentation of an object in image data, generating at least one seed point on the pre-segmentation from an intersection of the contour and the pre-segmentation, providing a weighting factor between the seed points and the pre-segmentation, and segmenting the pre-segmentation using the seed points and the weighting factor to generate a new pre-segmentation. | 12-18-2008 |

20090010515 | Robust Reconstruction Method for Parallel Magnetic Resonance Images - Methods and systems for reconstruction of an image from parallel Magnetic Resonance Image (pMRI) data are disclosed. A reconstructed pMRI image may suffer from noise and aliasing. A method for reducing aliasing by applying a bounded error function is disclosed. A method for reducing noise in a reconstruction by applying an error term is also disclosed. Error terms are included in an expression that can be solved as a minimization problem. Creating a solution in an iterative way is also disclosed. Examples of specific solutions are provided. A system applying the methods is also provided. | 01-08-2009 |

20090060333 | Interactive Image Segmentation On Directed Graphs - Methods for segmentation of an object from a background in an image are disclosed. Segmentation is achieved by an adapted Random Walker segmentation method using directed edges in a graph. The segmentation applies the minimization of an approximation of an energy function. A minimizer of the approximated energy function can be found by using iterative steps. Weights are assigned to an edge between two nodes. The weights are dependent on the direction of an edge. A system for segmentation of an object from a background is also disclosed. | 03-05-2009 |

20090097727 | 3D General Lesion Segmentation In CT - A general purpose method to segment any kind of lesions in 3D images is provided. Based on a click or a stroke inside the lesion from the user, a distribution of intensity level properties is learned. The random walker segmentation method combines multiple 2D segmentation results to produce the final 3D segmentation of the lesion. | 04-16-2009 |

20090190833 | Piecewise Smooth Mumford-Shah on an Arbitrary Graph - A method for recovering a contour using combinatorial optimization includes receiving an input image, initializing functions for gradient f, smooth background g, and contour r, determining an optimum of the gradient f of a region R in the input image, extending the optimum of the gradient f of region R to a complement of R, determining an optimum of the smooth background function g for a region Q corresponding to the complement of R, extending the optimum of the smooth background function g of region Q to a complement of Q, and determining an optimum contour r according to the optimum of the gradient f and the optimum of the smooth background function g. | 07-30-2009 |

20090268966 | IDENTIFICATION, CLASSIFICATION AND COUNTING OF TARGETS OF INTEREST IN MULTISPECTRAL IMAGE DATA - An imaging system for detecting targets of interest (TOIs) in multispectral imaging data includes a memory device storing a plurality of instructions embodying the system for detecting TOIs, a processor for receiving the multispectral imaging data and executing the plurality of instructions to perform a method including determining a list of events collocated across images of the multispectral imaging data and labeling each event as one of a TOI or non-TOI. | 10-29-2009 |

20100002925 | Fluid Dynamics Approach To Image Segmentation - A method for segmenting image data within a data processing system includes acquiring an image. One or more seed points are established within the image. An advection vector field is computed based on image influences and user input. A dye concentration is determined at each of a plurality of portions of the image that results from a diffusion of dye within the computed advection field. The image is segmented into one or more regions based on the determined dye concentration for the corresponding dye. | 01-07-2010 |

20100011268 | SYSTEM AND METHOD FOR SIGNAL RECONSTRUCTION FROM INCOMPLETE DATA - A method for reconstructing a signal from incomplete data in a signal processing device includes acquiring incomplete signal data. An initial reconstruction of the incomplete signal data is generated. A reconstruction is generated starting from the initial reconstruction by repeating the steps of: calculating a sparsity transform of the reconstruction, measuring an approximation of sparsity of the reconstruction by applying an m-estimator to the calculated sparsity transform, and iteratively optimizing the reconstruction to minimize output of the m-estimator thereby maximizing the approximation of sparsity for the reconstruction. The optimized reconstruction is provided as a representation of the incomplete data. | 01-14-2010 |

20100104186 | SYSTEM AND METHOD FOR IMAGE SEGMENTATION USING CONTINUOUS VALUED MRFS WITH NORMED PAIRWISE DISTRIBUTIONS - A method for segmenting a digital image includes initializing object and background seed nodes in an image, where the image is represented as a graph G=(V, E) whose nodes iεV correspond to image points and whose edges eεE connect adjacent points, where set M⊂V contains locations of nodes marked as seeds, set U⊂V contains locations of unmarked nodes, set O⊂M contains locations of object seed nodes, and set B⊂M contains locations of background seed nodes, assigning to each seed node a membership value such that ∀iεO,x | 04-29-2010 |

20100266170 | Methods and Systems for Fully Automatic Segmentation of Medical Images - Methods and systems dedicated to automatic object segmentation from image data are provided. In a first step a fuzzy seed set is generated that is learned from training data. The fuzzy seed set is registered to image data containing an object that needs to be segmented from a background. In a second step a random walker segmentation is applied to the image data by using the fuzzy seed set as an automatic seeding for segmentation. Liver segmentation, lung segmentation and kidney segmentation examples are provided. | 10-21-2010 |

20100308824 | METHOD FOR RECONSTRUCTING IMAGES OF AN IMAGED SUBJECT FROM A PARALLEL MRI ACQUISITION - A parallel MR imaging method that uses a reconstruction algorithm that combines the GRAPPA image reconstruction method and the compressed sensing (CS) image reconstruction method in an iterative approach ( | 12-09-2010 |

20110050703 | METHOD AND SYSTEM FOR INTERACTIVE SEGMENTATION USING TEXTURE AND INTENSITY CUES - A method for processing image data for segmentation includes receiving image data. One or more seed points are identified within the image data. Intensity and texture features are computer based on the received image data and the seed points. The image data is represented as a graph wherein each pixel of the image data is represented as a node and edges connect nodes representative of proximate pixels of the image data and establishing edge weights for the edges of the graph using a classifier that takes as input, one or more of the computed image features. Graph-based segmentation such as segmentation using the random walker approach may then be performed based on the graph representing the image data. | 03-03-2011 |

20110295515 | METHODS AND SYSTEMS FOR FAST AUTOMATIC BRAIN MATCHING VIA SPECTRAL CORRESPONDENCE - Methods and systems determine a correspondence of two sets of data, each data set represents an object. A weighted graph is created from each data set, and a Laplacian is determined for each weighted graph, from which spectral components are determined. The spectral components determine a coordinate of a node in a weighted graph. Nodes of a weighted graph are weighted with a quantified feature related to anode. A coordinate related to a quantified feature of a node is added to the coordinate based on the spectral components. Spectral components related to a weighted graph are reordered to a common ordering. Reordered spectral components related to the first and second data set are aligned and a correspondence is determined. An object may be a brain and a feature may be a sulcal depth. Other objects for which a correspondence may be determined include an electrical network, an image and a social network. | 12-01-2011 |

20120057765 | System and Method for Image Denoising Optimizing Object Curvature - A method for removing noise from an image includes receiving image data including a plurality of pixels. A graph including a plurality of nodes and a plurality of edges interconnecting the nodes is formulated. Each pixel of the image data is represented as a node of the graph and each edge of the graph is assigned a weight based on a penalty function applied to the nodes connected by the edge where the penalty function is less when a value of a given pixel of the plurality of pixels is between or equal to the values of two neighboring pixels than when the value of the given pixel is either greater than or less than the values of both of the two neighboring pixels. A total penalty of the graph is minimized. A denoised image is provided based on the total penalty-minimized graph. | 03-08-2012 |

20120081114 | System for Accelerated MR Image Reconstruction - An MR imaging system uses the multiple RF coils for acquiring corresponding multiple image data sets of the slice. An image data processor comprises at least one processing device conditioned for, generating a composite MR image data set representing a single image in a single non-iterative operation by performing a weighted combination of luminance representative data of individual corresponding pixels of the multiple image data sets in providing an individual pixel luminance value of the composite MR image data set. The image data processor reduces noise in the composite MR image data set by generating a reduced set of significant components in a predetermined transform domain representation of data representing the composite image to provide a de-noised composite MR image data set. An image generator comprises at least one processing device conditioned for, generating a composite MR image using the de-noised composite MR image data set. | 04-05-2012 |

20120314949 | System and Method for Image Segmentation by Optimizing Weighted Curvature - A method for segmenting an object in a digital image includes computing, for each point v | 12-13-2012 |

20130046759 | CONNECTING QUESTIONS, ANSWERS, ANNOUNCEMENTS AND ACTIVITIES TO RELEVANT ENTITIES - A method for brokering information includes receiving an initiator produced system activity, scoring a relevance of the system activity with each of a plurality of subscriber-specified thresholds, and transmitting an activity response to a subscriber activity feed in response to the system activity, the subscriber activity feed selected according to the relevance of a corresponding subscriber-specified threshold. | 02-21-2013 |

20130064439 | Systems and Method for Automatic Prostate Localization in MR Images Using Random Walker Segmentation Initialized Via Boosted Classifiers - Automatic prostate localization in T2-weighted MR images facilitate labor-intensive cancer imaging techniques. Methods and systems to accurately segment the prostate gland in MR images are provided and address large variations in prostate anatomy and disease, intensity inhomogeneities, and artifacts induced by endorectal coils. A center of the prostate is automatically detected with a boosted classifier trained on intensity based multi-level Gaussian Mixture Model Expectation Maximization (GMM-EM) segmentations of the raw MR images. A shape model is used in conjunction with Multi-Label Random Walker (MLRW) to constrain the seeding process within MLRW. | 03-14-2013 |