Abstract: A method is provided for detecting lesions in ultrasound images. The method includes acquiring ultrasound information, determining discriminative descriptors that describe the texture of a candidate lesion region, and classifying each of the discriminative descriptors as one of a top boundary pixel, a lesion interior pixel, a lower boundary pixel, or a normal tissue pixel. The method also includes determining a pattern of transitions between the classified discriminative descriptors, and classifying the candidate lesion region as a lesion or normal tissue based on the pattern of transitions between the classified discriminative descriptors.

Abstract: The present disclosure relates to characterization of biological samples. By way of example, a biological sample may be contacted with a plurality of probes specific for targets in the sample, such as probes for immune markers and segmenting probes. Acquired image data of the sample may be used to segment the images into epithelial and stromal regions to characterize individual cells in the sample based on the binding of the probes. Further, the biological sample may be characterized by a heterogeneity of the characterized cells.

Abstract: The present disclosure relates to characterization of biological samples. By way of example, a biological sample may be contacted with a plurality of probes specific for targets in the sample, such as probes for immune markers and segmenting probes. Acquired image data of the sample may be used to segment the images into epithelial and stromal regions to characterize individual cells in the sample based on the binding of the probes. Further, the biological sample may be characterized by a heterogeneity of the characterized cells.

Abstract: Dynamic linking of pathway maps and cell maps is disclosed in certain embodiments. In such embodiments, the pathway maps are linked to spatially-localized regional nucleic acid data (e.g., sequence data), as opposed to non-spatially selected nucleic acid data. The pathway map and cell map data may be linked so that interactions results in changes or updates to the linked map, such as the selection or highlighting of cells exhibiting pathway map characteristics specified by a user of updating of node values or states to correspond to that of a cell or cells selected by the user.

Abstract: Dynamic linking of pathway maps and cell maps is disclosed in certain embodiments. In such embodiments, the pathway maps are linked to spatially-localized regional nucleic acid data (e.g., sequence data), as opposed to non-spatially selected nucleic acid data. The pathway map and cell map data may be linked so that interactions results in changes or updates to the linked map, such as the selection or highlighting of cells exhibiting pathway map characteristics specified by a user of updating of node values or states to correspond to that of a cell or cells selected by the user.

Abstract: Exemplary embodiments include methods, systems, and devices for enabling users to provide quality scores for indicating the quality of image analysis methods performed on images of biological tissue. An exemplary user interface displays results of an image analysis method performed on an image of biological tissue in an overlaid manner on an image of biological tissue. The exemplary user interface enable a user to provide, directly on the user interface, one or more quality scores to indicate the user's assessment of the quality of the image analysis performed on the image. Exemplary embodiments store the quality scores provided by the user in association with the image analysis method and the image of biological tissue.

Abstract: A method is provided for detecting lesions in ultrasound images. The method includes acquiring ultrasound information, determining discriminative descriptors that describe the texture of a candidate lesion region, and classifying each of the discriminative descriptors as one of a top boundary pixel, a lesion interior pixel, a lower boundary pixel, or a normal tissue pixel. The method also includes determining a pattern of transitions between the classified discriminative descriptors, and classifying the candidate lesion region as a lesion or normal tissue based on the pattern of transitions between the classified discriminative descriptors.

Abstract: Systems and methods are disclosed for jointly presenting and analyzing morphological characteristics and biomarker expression levels of a biological sample. The systems and methods may utilize a morphological selection component to isolate a population of biological particles in a biological sample for exclusion from further processing. In addition, the systems and methods may simultaneously render morphological and statistical representations of the biological sample on a user interface.

Abstract: Embodiments disclosed herein include methods, systems, and devices for determining a positive or negative correlation between a clinical outcome and one or more features of biological tissue. An exemplary user interface enables a user to select a clinical outcome and one or more aspects of a displayed field-of-view of biological tissue. Exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of the user-selected aspects of the field-of-view of biological tissue. For example, exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of one or more biological units in the biological tissue.

Abstract: Systems and methods are disclosed for selecting a field of view for a biological sample, selecting first and second biomarkers, each having a corresponding image in a multiplexed biomarker image of the selected field of view, automatically analyzing expression level criterion for each of the first and second biomarkers, rendering the corresponding images of the selected field-of-view in an overlaid manner on the graphical user interface and highlighting a first set of biological units in the biological tissue that meets both the biomarker expression level criterion for both the first and second biomarkers.

Abstract: Exemplary embodiments enable selection and overlaid display of the expression of one or more biomarkers and/or one or more DNA sequences in a field-of-view of a biological tissue. The expressions of the biomarkers and/or DNA sequences are represented in one or more user-selected colors. The color settings are stored in associated with the biomarkers and/or DNA sequences such that a first user-selected color associated with a first biomarker in the saved color settings is automatically selected in response to receiving user input selecting the first biomarker. Similarly, a second user-selected color associated with a first DNA sequence in the saved color settings is automatically selected in response to receiving user input selecting the first DNA sequence.

Abstract: Systems and methods are disclosed for jointly presenting and analyzing morphological characteristics and biomarker expression levels of a biological sample. The systems and methods may utilize a morphological selection component to isolate a population of biological particles in a biological sample for exclusion from further processing. In addition, the systems and methods may simultaneously render morphological and statistical representations of the biological sample on a user interface.

Abstract: Exemplary embodiments include methods, systems, and devices for enabling users to provide quality scores for indicating the quality of image analysis methods performed on images of biological tissue. An exemplary user interface displays results of an image analysis method performed on an image of biological tissue in an overlaid manner on an image of biological tissue. The exemplary user interface enable a user to provide, directly on the user interface, one or more quality scores to indicate the user's assessment of the quality of the image analysis performed on the image. Exemplary embodiments store the quality scores provided by the user in association with the image analysis method and the image of biological tissue.

Abstract: Embodiments disclosed herein include methods, systems, and devices for determining a positive or negative correlation between a clinical outcome and one or more features of biological tissue. An exemplary user interface enables a user to select a clinical outcome and one or more aspects of a displayed field-of-view of biological tissue. Exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of the user-selected aspects of the field-of-view of biological tissue. For example, exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of one or more biological units in the biological tissue.

Abstract: A technique is provided for automatically generating a bone mask in CTA angiography. In accordance with the technique, an image data set may be pre-processed to accomplish a variety of function, such as removal of image data associated with the table, partitioning the volume into regionally consistent sub-volumes, computing structures edges based on gradients, and/or calculating seed points for subsequent region growing. The pre-processed data may then be automatically segmented for bone and vascular structure. The automatic vascular segmentation may be accomplished using constrained region growing in which the constraints are dynamically updated based upon local statistics of the image data. The vascular structure may be subtracted from the bone structure to generate a bone mask. The bone mask may in turn be subtracted from the image data set to generate a bone-free CTA volume for reconstruction of volume renderings.

Abstract: A technique is provided for partitioning an imaged volume into two or more sub-volumes. The technique identifies partition lines which separate the sub-volumes by generating a profile, such as a bone profile, which is then analyzed to determine the placement of the partition lines. In one embodiment, placement of the partition lines is determined automatically by applying one or more sets of hierarchical rules to the profile. After separation of the imaged volume into sub-volumes, each sub-volume may be differentially segmented such that segmentation is customized for the sub-volume. Likewise, after separation of the imaged volume into sub-volumes, the acquisition parameters for each sub-volume may be customized for subsequent acquisitions.

Abstract: A technique is provided for automatically identifying regions of bone or other structural regions within a reconstructed CT volume data set. The technique identifies and labels regions within the data set and computes various statistics for the regions. A rule-based classifier processes the statistics to classify each region. Incidental connections between disparate regions are eliminated. A structure mask, such as a bone mask, is then constructed after exclusion of regions of interest, such as a vascular map. The structure mask may then be used to construct a volume rendering free of the structure, such as bone-free.

Abstract: A technique is provided for automatically generating a bone mask in CTA angiography. In accordance with the technique, an image data set may be pre-processed to accomplish a variety of function, such as removal of image data associated with the table, partitioning the volume into regionally consistent sub-volumes, computing structures edges based on gradients, and/or calculating seed points for subsequent region growing. The pre-processed data may then be automatically segmented for bone and vascular structure. The automatic vascular segmentation may be accomplished using constrained region growing in which the constraints are dynamically updated based upon local statistics of the image data. The vascular structure may be subtracted from the bone structure to generate a bone mask. The bone mask may in turn be subtracted from the image data set to generate a bone-free CTA volume for reconstruction of volume renderings.

Abstract: A technique is provided for automatically identifying regions of bone or other structural regions within a reconstructed CT volume data set. The technique identifies and labels regions within the data set and computes various statistics for the regions. A rule-based classifier processes the statistics to classify each region. Incidental connections between disparate regions are eliminated. A structure mask, such as a bone mask, is then constructed after exclusion of regions of interest, such as a vascular map. The structure mask may then be used to construct a volume rendering free of the structure, such as bone-free.

Abstract: A technique is provided for partitioning an imaged volume into two or more sub-volumes. The technique identifies partition lines which separate the sub-volumes by generating a profile, such as a bone profile, which is then analyzed to determine the placement of the partition lines. In one embodiment, placement of the partition lines is determined automatically by applying one or more sets of hierarchical rules to the profile. After separation of the imaged volume into sub-volumes, each sub-volume may be differentially segmented such that segmentation is customized for the sub-volume. Likewise, after separation of the imaged volume into sub-volumes, the acquisition parameters for each sub-volume may be customized for subsequent acquisitions.