Abstract: Methods and apparatus for improved deep learning for image acquisition are provided. An imaging system configuration apparatus includes a training learning device including a first processor to implement a first deep learning network (DLN) to learn a first set of imaging system configuration parameters based on a first set of inputs from a plurality of prior image acquisitions to configure at least one imaging system for image acquisition, the training learning device to receive and process feedback including operational data from the plurality of image acquisitions by the at least one imaging system. The example apparatus includes a deployed learning device including a second processor to implement a second DLN, the second DLN generated from the first DLN of the training learning device, the deployed learning device configured to provide a second imaging system configuration parameter to the imaging system in response to receiving a second input for image acquisition.

Abstract: Methods and apparatus for monitoring and improving imaging system operation are provided. An example apparatus includes a first deployed deep learning network (DLN) which operates with an acquisition engine to generate an imaging device configuration. The example apparatus includes a second deployed DLN which operates with a reconstruction engine based on acquired image data. The example apparatus includes a first assessment engine with a third deployed DLN. The assessment engine receives output from at least one of the acquisition engine or the reconstruction engine to assess operation of the respective at least one of the acquisition engine or the reconstruction engine and to provide feedback to the respective at least one of the acquisition engine or the reconstruction engine. The first deployed DLN and the second deployed DLN are generated and deployed from first and second training DLNS, respectively.

Abstract: Methods and apparatus to automatically generate an image quality metric for an image are provided. An example method includes automatically processing a first medical image using a deployed learning network model to generate an image quality metric for the first medical image, the deployed learning network model generated from a digital learning and improvement factory including a training network, wherein the training network is tuned using a set of labeled reference medical images of a plurality of image types, and wherein a label associated with each of the labeled reference medical images indicates a central tendency metric associated with image quality of the image. The example method includes computing the image quality metric associated with the first medical image using the deployed learning network model by leveraging labels and associated central tendency metrics to determine the associated image quality metric for the first medical image.

Abstract: Methods and apparatus for determining brain cortical thickness are provided. One method includes determining an intensity profile at each of a plurality of cortical surface points of an imaged brain using brain tissue image data and calculating a cortical thickness based on a parametrically determined transition point of each intensity profile.

Abstract: A method for navigating a three-dimensional (3D) image includes accessing a 3D image dataset, generating a 3D mesh corresponding to a 3D segmentation result using the 3D image dataset, displaying a 3D surface rendering of the 3D surface mesh, and navigating the 3D image based on a manual input received from a user indicated on the rendered 3D mesh.

Abstract: Certain examples provide systems and methods for holistic viewing to provide comparative analysis and decision support in a drug development process. An example method includes a computer-implemented method for assessing drug efficacy, comprising: accessing a first data set related to the performance of a target drug for a given indication; accessing a second data set related to a control for the indication; comparing the data for the target drug and the data for the control on at least one of a plurality of different metrics using a holistic analysis, wherein the at least one metric corresponds to an outcome associated with the indication and generating a corresponding report.

Abstract: A method is provided for segmenting three-dimensional (3D) image volumes. The method includes obtaining a 3D volume data set corresponding to an imaged volume, rendering at least a portion of the 3D volume data set based on 3D rendering settings, and creating a two-dimensional (2D) segmentation of the rendered 3D volume data set. The method further includes segmenting the 3D volume data set using the 2D segmentation and the 3D rendering settings to define a 3D region of interest within the 3D volume data set.

Abstract: A method for extracting a three-dimensional (3D) volume of interest from a three-dimensional (3D) image dataset includes accessing a 3D image dataset that includes a plurality of image slices, enclosing a 3D volume of interest in the 3D image dataset using a 3D mesh, automatically extracting the 3D volume of interest based on the 3D mesh, and generating a 3D image of the extracted 3D volume of interest. A computer and a non-transitory computer readable medium are also described herein.

Abstract: A method for navigating a three-dimensional (3D) image includes accessing a 3D image dataset, generating a 3D mesh corresponding to a 3D segmentation result using the 3D image dataset, displaying a 3D surface rendering of the 3D image intensities on the 3D mesh, and navigating the 3D image based on a manual input received from a user indicated on the rendered 3D image.

Abstract: A method for extracting a three-dimensional (3D) volume of interest from a three-dimensional (3D) image dataset includes accessing a 3D image dataset that includes a plurality of image slices, enclosing a 3D volume of interest in the 3D image dataset using a 3D mesh, automatically extracting the 3D volume of interest based on the 3D mesh, and generating a 3D image of the extracted 3D volume of interest. A computer and a non-transitory computer readable medium are also described herein.

Abstract: A method for navigating a three-dimensional (3D) image includes accessing a 3D image dataset, generating a 3D mesh corresponding to a 3D segmentation result using the 3D image dataset, displaying a 3D surface rendering of the 3D surface mesh, and navigating the 3D image based on a manual input received from a user indicated on the rendered 3D mesh.

Abstract: A method is provided for segmenting three-dimensional (3D) image volumes. The method includes obtaining a 3D volume data set corresponding to an imaged volume, rendering at least a portion of the 3D volume data set based on 3D rendering settings, and creating a two-dimensional (2D) segmentation of the rendered 3D volume data set. The method further includes segmenting the 3D volume data set using the 2D segmentation and the 3D rendering settings to define a 3D region of interest within the 3D volume data set.

Abstract: Certain examples provide systems and methods for holistic viewing to provide comparative analysis and decision support in a drug development process. An example method includes a computer-implemented method for assessing drug efficacy, comprising: accessing a first data set related to the performance of a target drug for a given indication; accessing a second data set related to a control for the indication; comparing the data for the target drug and the data for the control on at least one of a plurality of different metrics using a holistic analysis, wherein the at least one metric corresponds to an outcome associated with the indication and generating a corresponding report.

Abstract: Certain examples provide systems and methods for holistic viewing to provide comparative analysis and decision support in a drug development process, and safety testing. An example method includes providing a first set of data corresponding to a drug of interest; providing a reference set of drug interaction data, comparing the first set of data to the reference set using a holistic analysis, and reporting the results of the comparison. An example of the holistic analysis and viewing apparatus for drug safety comprises a standardizer to at least one of standardize and normalize drug interaction data related to drug safety; a deviation analyzer to compare the drug interaction data to data corresponding to a drug under review using a holistic analysis, and a reporter for reporting the output of the deviation analyzer.

Abstract: Certain examples provide systems and methods for holistic viewing to provide comparative analysis and decision support in a drug development process. An example method includes accessing data related to drug development; pre-processing the data to prepare the data for measurement and analysis; and analyzing the data based on at least one of a plurality of different metrics. Each metric corresponds to a quantified variation between a first data set of results corresponding to a category in the drug development process. The first data set of results is provided for comparison with a second data set of results corresponding to at least one other category in the drug development process. At least some of the plurality of metrics are aggregated to generate a visual representation representing an integrated comparative visualization for the identified category.

Abstract: Systems, methods and computer-readable storage mediums encoded with instructions for providing touch-driven controls in a clinical setting are provided. Certain embodiments provide a system that includes a clinical system and a customizable structured library of functions. The structured library can include a function associated with a clinical context. The function can be associated with a user input requiring the use of a touch driven interface with multi-touch gestures. The user input can provide for immediate execution of the associated function. The structured library can be loaded onto the clinical system as a driver such that the function is made available based on the associated clinical context. Certain embodiments can include a user interface configured to allow a user to add or delete a function or modify the user input associated with a function. Certain embodiments can include a user interface that provides instruction as to using a function.

Abstract: Systems, methods and mediums with instructions for viewing medical data are provided. A system for viewing medical data can include a computer processor, a database and a user interface. The database can include numerous entries from numerous clinical modalities. Each entry can include image data and/or non-image data. Each entry can include annotated medical information from a previous study. The annotated medical information can include comments and markings. The database can be searchable to identify an entry based on input medical information relating to a current study. The user interface can be configured to simultaneously display annotated medical information from an identified entry and medical information from the current study. The system can further include a second user interface configured to display medical information, allow a user to annotate the medical information, and allow the user to save the annotated medical information as an entry in the database.

Abstract: A method and system for visualizing monochromatic images in color hue is disclosed herewith. The method comprises: obtaining an optimal monochromatic color wavelength corresponding to an effective light level, the effective light level being identified with reference to an ambient light level and a monitor light level. The monochromatic color wavelength is converted to corresponding to a color hue and is incorporated to a gray scale map of an image to provide a colored view of the image.

Abstract: Methods and apparatus for determining brain cortical thickness. One method includes determining an intensity profile at each of a plurality of cortical surface points of an imaged brain using brain tissue image data and calculating a cortical thickness based on a parametrically determined transition point of each intensity profile.

Abstract: In one embodiment, a computer assisted method for displaying a medical image is provided. The method comprises steps of determining authorization status of a user accessing an image database, suppressing the information content in a first image, commensurate with the authorization status, to obtain a second image and displaying the second image to the user.