Abstract: A system receives content of a memory resource. The system compares the content of the memory resource with a first resource data associated with a first physical space, and with a second resource data associated with a second physical space. The system determines which of the first physical space and the second physical space can fulfill more than a threshold percentage of objects in the memory resource based on the comparison between the content of the memory resource with the first and second resource data. The system determines that the first physical space can fulfill more than the threshold percentage of objects in the memory resource. The system assigns the first physical space to the memory resource for concluding an operation associated with the memory resource.

Abstract: A system for selecting delivery mechanisms sends a request to a plurality of servers associated with one or more autonomous delivery mechanism and one or more non-autonomous delivery mechanisms to provide delivery metadata. The request comprises a pickup location coordinate and a delivery location coordinate. The delivery metadata comprises a delivery time and a delivery quote. The system receives a first set of delivery metadata associated with one or more autonomous delivery mechanisms, and a second set of delivery metadata associated with one or more non-autonomous delivery mechanisms. The system identifies a particular autonomous delivery mechanism from within the category of autonomous delivery mechanisms based on the first set of delivery metadata. The system identifies a particular non-autonomous delivery mechanism from within the category of non-autonomous delivery mechanisms based on the second set of delivery metadata.

Abstract: A system generates a set of instructions for preparing content of a memory resource that comprises a set of objects in a particular sequence. The system sends the content of the memory resource and the set of instructions to a user device. The system receives a first message that indicates the set of objects is being prepared from the user device. The system sends, to a server associated with a delivery vehicle, a third message to alert the delivery vehicle to pick up the set of objects from a pickup location and deliver to a delivery location coordinate. The system receives, from the server, an alert message that indicates the delivery vehicle has reached the pickup location coordinate. The system forwards the alert message to the user device.

Abstract: A system presents a plurality of objects on a delivery user interface. The system updates content of a memory resource as one or more objects are added to the memory resource. In response to determining that the content of the memory resource is finalized, the system determines a selection of a particular autonomous delivery mechanism and a particular non-autonomous delivery mechanism based on filtering conditions associated with the content of the memory resource. The system presents the selection of the particular autonomous delivery mechanism and the particular non-autonomous delivery mechanism on a delivery user interface. The system determines that a delivery mechanism is selected from the selection. The system receives one or more status updates associated with the selected delivery mechanism, and displays the one or more status updates on the delivery user interface.

Abstract: A system sends a drop-off location coordinate to a server associated with a delivery mechanism. The system receives, from the server, a hyperlink that upon access, the drop-off location coordinate is displayed on a virtual map. The system links the hyperlink to an adjust drop-off location element, such that when the adjust drop-off element is accessed, the virtual map is displayed within a delivery user interface. The system integrates the adjust drop-off element into the delivery user interface such that the adjust drop-off element is accessible from within the delivery user interface.

Abstract: A system receives content of a memory resource. The system compares the content of the memory resource with a first resource data associated with a first physical space, and with a second resource data associated with a second physical space. The system determines which of the first physical space and the second physical space can fulfill more than a threshold percentage of objects in the memory resource based on the comparison between the content of the memory resource with the first and second resource data. The system determines that the first physical space can fulfill more than the threshold percentage of objects in the memory resource. The system assigns the first physical space to the memory resource for concluding an operation associated with the memory resource.

Abstract: According to one embodiment, workflow templates are maintained, each workflow template including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. In response to a request for processing medical image data from a user, a user identifier (ID) that identifies the user is automatically determined based on the request. At least one of the workflow templates that is specifically configured to process medical image data associated with the user is identified based on the user ID. One or more image processing operations defined by the identified workflow template are performed on the medical image data, generating a scene corresponding to an image view representing the medical image data. The scene associated with each of the workflow stages is stored in a persistent storage, where a scene includes metadata used to recreate a corresponding medical image view subsequently.

Abstract: According to one embodiment, workflow templates are maintained, each workflow template including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. In response to a request for processing medical image data from a user, a user identifier (ID) that identifies the user is automatically determined based on the request. At least one of the workflow templates that is specifically configured to process medical image data associated with the user is identified based on the user ID. One or more image processing operations defined by the identified workflow template are performed on the medical image data, generating a scene corresponding to an image view representing the medical image data. The scene associated with each of the workflow stages is stored in a persistent storage, where a scene includes metadata used to recreate a corresponding medical image view subsequently.

Abstract: According to one embodiment, workflow templates are maintained, each workflow template including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. In response to a request for processing medical image data from a user, a user identifier (ID) that identifies the user is automatically determined based on the request. At least one of the workflow templates that is specifically configured to process medical image data associated with the user is identified based on the user ID. One or more image processing operations defined by the identified workflow template are performed on the medical image data, generating a scene corresponding to an image view representing the medical image data. The scene associated with each of the workflow stages is stored in a persistent storage, where a scene includes metadata used to recreate a corresponding medical image view subsequently.

Abstract: According to one embodiment, workflow templates are stored, each including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. Each workflow stage defines one or more image processing operations to be performed. At least one workflow stage generates metadata specifying a parameter to be used by another workflow stage for processing a corresponding medical image. In response to medical image data received, at least one of the image processing operations defined by the workflow stages is performed on the medical image data. A scene is generated for each of the workflow stages representing an image view representing the medical image data. In response to a save or validate command received from a user, the scene associated with each of the workflow stages is stored in a persistent storage, which can be used to recreate a corresponding medical image view subsequently.

Abstract: A digital medical assistant is configured to obtain authorization of a service request. The assistant includes: an input for receiving an electronic medical record (EMR) of a patient and identity of a benefit provider for the patient; a preauthorization engine configured for completing an application by identifying relevant clinical context from the EMR and correlating the relevant clinical context with preauthorization criteria; the preauthorization engine further configured for submitting a completed application as the request to the benefit provider, receiving a decision from the provider, and outputting the decision. A method of use in a computer program product are provided.

Abstract: Some embodiments of a workflow management system to process medical image data generated by a medical imaging device have been presented. In one embodiment, a user selects a workflow template with a predefined set of image processing stages, and applies the workflow template to the medical image data. Each of the predefined set of image processing stages in the workflow template includes one or more image processing operations. Each of the image processing operations is capable of generating metadata for processing the medical image data. The medical image data is then processed through each of the predefined image processing stages. The result of processing is a collection of metadata. Each metadata in the collection can be applied to the medical image data to generate a medical image view.

Abstract: Some embodiments of a workflow management system to process medical image data generated by a medical imaging device have been presented. In one embodiment, a user selects a workflow template with a predefined set of image processing stages, and applies the workflow template to the medical image data. Each of the predefined set of image processing stages in the workflow template includes one or more image processing operations. Each of the image processing operations is capable of generating metadata for processing the medical image data. The medical image data is then processed through each of the predefined image processing stages. The result of processing is a collection of metadata. Each metadata in the collection can be applied to the medical image data to generate a medical image view.

Abstract: A three-dimensional medical image display system comprises a pre-processing device that includes data analysis device and a data processing device. The pre-processing device inputs a set of medical image data created by a scan performed by a medical imaging device. The data analysis device determines a set of analytic protocols for processing the image data by analyzing the image data. The data processing device processes the image data according to a protocol and a corresponding set of parameters identified by the data analysis device.

Abstract: A three-dimensional image processing system enables multiple users at distant locations employing ordinary personal computers to construct and observe three-dimensional images simultaneously. In a network environment, a three-dimensional image processing device acquires image data and incorporates it into three-dimensional voxels based on instructions from the computers. The device operates on the three-dimensional voxels using object space domain, opacity and color parameters to construct three-dimensional data and operates on the three-dimensional data using projection processing parameters to construct three-dimensional images. The system sets projection processing parameters for constructing three-dimensional images from three-dimensional data and displays three-dimensional images which may be routed to the various computers via the network.

Abstract: A method renders a volume data set as an image in a volume rendering system. The volume data set includes a plurality of voxels stored in a memory. The volume rendering system includes a plurality of parallel processing pipelines. The image includes a plurality of pixels stored in the memory. A set of rays are cast through the volume data set. The volume data set is partitioned into a plurality of sections aligned with the sets of rays. Voxels along each ray of each set are sequentially interpolated voxels in only one of the plurality of pipelines to generate samples only as long as the samples contribute to the image.

Abstract: A three-dimensional image processing system enables multiple users at distant locations employing ordinary personal computers to construct and observe three-dimensional images simultaneously. In a network environment, a three-dimensional image processing device acquires image data and incorporates it into three-dimensional voxels based on instructions from the computers. The device operates on the three-dimensional voxels using object space domain, opacity and color parameters to construct three-dimensional data and operates on the three-dimensional data using projection processing parameters to construct three-dimensional images. The system sets projection processing parameters for constructing three-dimensional images from three-dimensional data and displays three-dimensional images which may be routed to the various computers via the network.

Abstract: A method generates a histogram of a volume data set in a rendering pipeline. The volume data set includes a plurality of samples stored in a memory. Each sample is partitioned in parallel into a plurality of field according to a plurality of format registers, there is one format register for each field. Entries of a plurality of tables are indexed in parallel with the plurality of fields, there is one entry indexed in each table by each field. The indexed entries are incremented to accumulate a histogram of the fields of the samples of the volume data set.

Abstract: A method maps samples in a rendering pipelines. The samples are stored in a sample memory. Each sample has a plurality of fields. A descriptor is stored for each field in a field format register. Each sample is read from the memory into a mapping unit. The fields are extracted from each sample according to the corresponding descriptor, and forwarded in parallel to the rendering pipeline.

Abstract: A volume rendering pipeline includes a plurality of processing stages such as a gradient estimation stage, an interpolation stage, a classification stage, an illumination stage, and a compositing stage. The stages are connected to each other by multiplexers. A first multiplexer connects an output of a first stage to an input of a second stage. A second multiplexer connects an output of the second stage to an input of the first stage. A third multiplexer has inputs connected to the output of the first stage and the output of the second stage, the first, second, and third multiplexers are responsive to a select signal to configure the stages of the rendering pipeline for processing the volume data set.