Abstract: Systems and methods for supporting a diagnostic workflow from a computer system are disclosed herein. In accordance with one implementation, a set of pre-identified anatomical landmarks associated with one or more structures of interest within one or more medical images are presented to a user. In response to a user input selecting at least one or more regions of interest including one or more of the pre-identified anatomical landmarks, the user is automatically navigated to the selected region of interest. In another implementation, a second user input selecting one or more measurement tools is received. An evaluation may be automatically determined based on one or more of the set of anatomical landmarks in response to the second user input.

Abstract: A method for synchronizing patient data between at least two independent applications in a distributed environment includes capturing screen information from a display window of a first application client that is displaying a medical image of a patient, analyzing the screen information captured from the first application client display to extract patient identifying information, and synchronizing a display of information of the patient on a second application system display screen with the first application display window using the extracted patient identification information.

Abstract: A system for providing automatic diagnosis and decision support includes: a medical image database; generative learning and modeling modules that build distributional appearance models and spatial relational models of organs or structures using images from the medical image database; a statistical whole-body atlas that includes one or more distributional appearance models and spatial relational models of organs or structure, in one or more whole-body imaging modalities, built by the generative learning and modeling modules; and discriminative learning and modeling modules that build two-class or multi-class classifiers for performing at least one of organ, structure or disease detection or segmentation.

Abstract: A method for detecting lymph nodes in a medical image includes receiving image data. One or more regions of interest are detected from within the received image data. One or more lymph node candidates are identified using a set of predefined parameters that is particular to the detected region of interest where each lymph node candidate is located. The identifying unit may identify the one or more lymph node candidates by performing DGFR processing. The method may also include receiving user-provided adjustments to the predefined parameters that are particular to the detected regions of interest and identifying the lymph node candidates based on the adjusted parameters. The lymph node candidates identified based on the adjusted parameters may be displayed along with the image data in real-time as the adjustments are provided.

Abstract: Systems and methods for performing a medical imaging study include acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.

Abstract: A method allowing for fast mapping between a content identifier (ID) for a media content file and the file path of said media content file includes: dividing a plurality of characters making up the contend ID into a plurality of ordered subsections separated by a separator character, correlating at least one of the subsections with a directory in an electronic file system, and correlating the last of the subsections with a name of the media content file, the media content file being located within a directory correlated with a preceding subsection.

Abstract: A method allowing for fast mapping between a content identifier (ID) for a media content file and the file path of said media content file includes: dividing a plurality of characters making up the contend ID into a plurality of ordered subsections separated by a separator character, correlating at least one of the subsections with a directory in an electronic file system, and correlating the last of the subsections with a name of the media content file, the media content file being located within a directory correlated with a preceding subsection.

Abstract: Systems and methods for supporting a diagnostic workflow from a computer system are disclosed herein. In accordance with one implementation, a set of pre-identified anatomical landmarks associated with one or more structures of interest within one or more medical images are presented to a user. In response to a user input selecting at least one or more regions of interest including one or more of the pre-identified anatomical landmarks, the user is automatically navigated to the selected region of interest. In another implementation, a second user input selecting one or more measurement tools is received. An evaluation may be automatically determined based on one or more of the set of anatomical landmarks in response to the second user input.

Abstract: A method for performing a medical imaging study includes acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.

Abstract: A system and method for linking volumes of interest (VOIs) across timepoints are provided. The method comprises: loading an image dataset of a first timepoint and an image dataset of a second timepoint; registering the image dataset of the first timepoint and the image dataset of the second timepoint; displaying the image dataset of the first timepoint and the image dataset of the second timepoint; selecting a VOI in the image dataset of the first timepoint and the image dataset of the second timepoint; and linking the VOIs in the image dataset of the first timepoint and the image dataset of the second timepoint.

Abstract: A computer system for automatic selection of a computer-aided detection (CAD) algorithm including a database storing image data, a browser for navigating the data and selecting image data, an application receiving image data selected by the browser, and a selector selecting a CAD algorithm for processing the image data according to at least one of fixed attributes of the image data and an indication of a subject of the image data.

Abstract: A system for computer aided detection and decision support includes an ontology of image representations for injecting meaning into and adding relationships among image contents, an image understanding and parsing module in communication with the ontology of image representations for extracting structures from an image including the image contents, and a reasoning engine based in communication with the ontology and the image understanding and parsing module for classifying the image contents, wherein the system receives the image and corresponding descriptive information.

Abstract: A method for registering a medical image includes acquiring a first medical image of a subject. One or more simulated medical images are synthesized based on the acquired first medical image. One or more matching functions are trained using the first medical image and the simulated medical images. A second medical image of the subject is acquired. The first medical image and the second medical image are registered using the one or more trained matching functions.

Abstract: A method for lesion detection includes acquiring pre-therapy medical image data from a first modality. Post-therapy medical image data is acquired from a second modality. A transformation matrix for transforming from an image space of the first modality to an image space of the second modality is calculated. A volume of interest is defined from the medical image data of the first modality. The volume of interest includes one or more lesions. The volume of interest is automatically copied to the medical image data of the second modality using the calculated transformation matrix. Treatment is directed to the lesion using the medical image data of the second modality including the copied volume of interest data.

Abstract: By testing for nodule segmentation errors based on the scan data, juxtapleural cases are identified. Once identified, the scan data or subsequent estimation may be altered to account for adjacent rib, tissue, vessel or other structure effecting segmentation. One alteration is to shape a filter as a function of the scan data. For example, an originally estimated ellipsoid for the nodule segmentation defines the filter. The filter is used to identify the undesired information, and masking removes the undesired information for subsequent estimation of the nodule segmentation. Another possible alteration biases the subsequent estimation away from the incorrect information, such as the rib, tissue or vessel information influencing the original estimation. For example, a negative prior or probability is assigned to data corresponding to the originally estimated segmentation for the subsequent estimation.

Abstract: Ingesting media on a content distribution network includes obtaining media content in a media content ingestion system, storing the media content on a home storage volume of a data storage structure, and replicating the media content across multiple storage volumes on the data storage structure based on a set of data associated with the media content.

Abstract: A method allowing for fast mapping between a content identifier (ID) for a media content file and the file path of said media content file includes: dividing a plurality of characters making up the contend ID into a plurality of ordered subsections separated by a separator character, correlating at least one of the subsections with a directory in an electronic file system, and correlating the last of the subsections with a name of the media content file, the media content file being located within a directory correlated with a preceding subsection.

Abstract: A system for storing content available for streaming includes a storage tier with a plurality of storage clusters, each of the storage clusters having at least one server, the storage clusters collectively storing multiple media content files; a streaming tier coupled to the storage tier, the streaming tier having multiple streaming servers, the streaming tier being configured to stream data over a network faster than the storage tier is able to stream the data over the network; and a computer-implemented synchronization module configured to analyze traffic statistics associated with a media content file stored on the storage tier and selectively replicate the media content file on the streaming tier based on the traffic statistics.

Abstract: Providing media content includes storing a plurality of media files on a storage tier having at least one storage cluster, each storage cluster having at least one server, replicating at least some of the media files stored on the storage tier on at least one streaming server of a streaming tier configured to stream data over a network faster than the storage tier is able to stream the data over the network; receiving a request from a client over the network for a portion of a selected media file; streaming the requested portion of the selected media file to the client from the streaming tier if the selected media file is stored on the streaming tier; and streaming the requested portion of the selected media file to the client from the storage tier if the media file is not stored on the streaming tier.

Abstract: A system for providing automatic diagnosis and decision support includes: a medical image database; generative learning and modeling modules that build distributional appearance models and spatial relational models of organs or structures using images from the medical image database; a statistical whole-body atlas that includes one or more distributional appearance models and spatial relational models of organs or structure, in one or more whole-body imaging modalities, built by the generative learning and modeling modules; and discriminative learning and modeling modules that build two-class or multi-class classifiers for performing at least one of organ, structure or disease detection or segmentation.