Patent application number | Description | Published |
20100049072 | METHOD AND APPARATUS FOR RETRIEVAL OF SIMILAR HEART SOUNDS FROM A DATABASE - The present invention exploits a visual rendering of heart sounds and models the morphological variations of audio envelopes through a constrained non-rigid translation transform. Similar heart sounds are then retrieved by recovering the corresponding alignment transform using a variant of shape-based dynamic time warping. | 02-25-2010 |
20110310964 | ECHOCARDIOGRAM VIEW CLASSIFICATION USING EDGE FILTERED SCALE-INVARIANT MOTION FEATURES - According to one embodiment of the present invention, a method for echocardiogram view classification is provided. According to one embodiment of the present invention, a method comprises: obtaining a plurality of video images of a subject; aligning the plurality images; using the aligned images to generate a motion magnitude image; filtering the motion magnitude image using an edge map on image intensity; detecting features on the motion magnitude image, retaining only those features which lie in the neighborhood of intensity edges; encoding the remaining features by generating, x, y image coordinates, a motion magnitude histogram in a window around the feature point, and a histogram of intensity values near the feature point; and using the encoded features to classify the video images of the subject into a predetermined classification. | 12-22-2011 |
20120020563 | Systems and Methods for Automated Extraction of Measurement Information in Medical Videos - Systems and methods providing automated extraction of information contained in video data and uses thereof are described. In particular, systems and associated methods are described that provide techniques for extracting data embedded in video, for example measurement-value pairs of medical videos, for use in a variety of applications, for example video indexing, searching and decision support applications. | 01-26-2012 |
20120288171 | ECHOCARDIOGRAM VIEW CLASSIFICATION USING EDGE FILTERED SCALE-INVARIANT MOTION FEATURES - According to one embodiment of the present invention, a method for echocardiogram view classification is provided. According to one embodiment of the present invention, a method comprises: obtaining a plurality of video images of a subject; aligning the plurality images; using the aligned images to generate a motion magnitude image; filtering the motion magnitude image using an edge map on image intensity; detecting features on the motion magnitude image, retaining only those features which lie in the neighborhood of intensity edges; encoding the remaining features by generating, x, y image coordinates, a motion magnitude histogram in a window around the feature point, and a histogram of intensity values near the feature point; and using the encoded features to classify the video images of the subject into a predetermined classification. | 11-15-2012 |
20120321189 | SYSTEMS AND METHODS FOR AUTOMATED EXTRACTION OF MEASUREMENT INFORMATION IN MEDICAL VIDEOS - Systems and methods providing automated extraction of information contained in video data and uses thereof are described. In particular, systems and associated methods are described that provide techniques for extracting data embedded in video, for example measurement-value pairs of medical videos, for use in a variety of applications, for example video indexing, searching and decision support applications. | 12-20-2012 |
20140270455 | Using RNAi Imaging Data For Gene Interaction Network Construction - Embodiments of the invention relate to a constructing a gene interaction network. Tools are provided to compute a gene relationship measure based upon cellular images, and to rank image collections having a similar morphology. The ranking is based upon capturing similarity within the ranked collection by modeling a three dimensional shape of a cellular image stack. The graph is constructed for related images stacks. Nodes in the graph represent genes, and edges drawn between the nodes represent corresponding image stacks in a commonly ranked list. Accordingly, the graphical representation mathematically and visually connects respective genes. | 09-18-2014 |
20140278128 | Combining RNAi Imaging Data With Genomic Data For Gene Interaction Network Construction - Embodiments of the invention relate to a method, system, and computer program product to construct a gene interaction network by combining two sources of genomic information, namely RNAi imaging data and gene expression data. Tools are provided to gather data, including gene expression data and gene image data, and to compute measurements and relationships, respectively. A graph is constructed with nodes representing genes and edges drawn between the nodes to form gene clusters. The graph is refined such that the shape captures a structural pattern of the cluster. | 09-18-2014 |
20140278131 | Combining RNAi Imaging Data With Genomic Data For Gene Interaction Network Construction - Embodiments of the invention relate to a method for constructing a gene interaction network by combining two sources of genomic information, namely RNAi imaging data and gene expression data. Tools are provided to gather data, including gene expression data and gene image data, and to compute measurements and relationships, respectively. A graph is constructed with nodes representing genes and edges drawn between the nodes to form gene clusters. The graph is refined such that the shape captures a structural pattern of the cluster. | 09-18-2014 |
20140278132 | Using RNAi Imaging Data For Gene Interaction Network Construction - Embodiments of the invention relate to a constructing a gene interaction network. Tools are provided to compute a gene relationship measure based upon cellular images, and to rank image collections having a similar morphology. The ranking is based upon capturing similarity within the ranked collection by modeling a three dimensional shape of a cellular image stack. The graph is constructed for related images stacks. Nodes in the graph represent genes, and edges drawn between the nodes represent corresponding image stacks in a commonly ranked list. Accordingly, the graphical representation mathematically and visually connects respective genes. | 09-18-2014 |