Abstract: Systems and methods to label structures of interest in tissue slide images are described.

Abstract: Systems and methods to train a cell object detector are described.

Abstract: Disclosed are techniques for external quiesce of a core in a multi-core system. In some aspects, a method for external quiesce of a core in a multi-core system-on-chip (SoC), comprises, at control circuitry for the multi-core SoC, receiving an indication that a core in a multi-core SoC should be quiesced, determining that the core should be externally quiesced, and asserting an external quiesce request input into the core.

Abstract: Systems and methods to label structures of interest in tissue slide images are described.

Abstract: Systems and methods to train a cell object detector are described.

Abstract: Approaches presented herein enable delivery of real-time internet of things (IoT) feedback to optimize a group discussion. More specifically, a set of data representing a discussion between users is captured and analyzed to generate a discussion profile that includes participation of the users. This profile is compared to a reference profile and, based on the comparison, a set of discussion participation improvement strategies for a user is generated. A strategy is selected from the set of discussion participation improvement strategies based on an identification of an availability of a set of IoT devices for delivery of the strategy. Instructions are then communicated, responsive to the captured discussion between the users, to an available IoT device to deliver the selected discussion participation improvement strategy to the user through an output user interface of the available IoT device during the discussion.

Abstract: Approaches presented herein enable delivery of real-time internet of things (IoT) feedback to optimize a group discussion. More specifically, a set of data representing a discussion between users is captured and analyzed to generate a discussion profile that includes participation of the users. This profile is compared to a reference profile and, based on the comparison, a set of discussion participation improvement strategies for a user is generated. A strategy is selected from the set of discussion participation improvement strategies based on an identification of an availability of a set of IoT devices for delivery of the strategy. Instructions are then communicated, responsive to the captured discussion between the users, to an available IoT device to deliver the selected discussion participation improvement strategy to the user through an output user interface of the available IoT device during the discussion.

Abstract: Systems and methods for analyzing vessels in multiplexed images include detecting large vessels using a spoke feature detection method, detecting long and narrow vessels using a line feature detection method, detecting smaller vessels using rolling-ball filtering and binary image operations to generate a mask, and evaluating any contour polygons resulting from these operations using quality measurements and other thresholds. Maturity determination and nuclei detection are also performed, resulting in an output of vessel characteristics and co-locations enabling enhanced analysis of multispectral images.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts risk of prostate cancer progression in a patient, where the model is based on features including one or more (e.g., all) of preoperative PSA, dominant Gleason Grade, Gleason Score, at least one of a measurement of expression of AR in epithelial and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei, and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area. In some embodiments, the morphometric information is based on image analysis of tissue subject to multiplex immunofluorescence and may include characteristic(s) of a minimum spanning tree (MST) and/or a fractal dimension observed in the images.

Abstract: In one embodiment, a processor includes a frontend unit having an instruction decoder to receive and to decode instructions of a plurality of threads, an execution unit coupled to the instruction decoder to receive and execute the decoded instructions, and an instruction retirement unit having a retirement logic to receive the instructions from the execution unit and to retire the instructions associated with one or more of the threads that have an instruction or an event pending to be retired. The instruction retirement unit includes a thread arbitration logic to select one of the threads at a time and to dispatch the selected thread to the retirement logic for retirement processing.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts risk of prostate cancer progression in a patient, where the model is based on features including one or more (e.g., all) of preoperative PSA, dominant Gleason Grade, Gleason Score, at least one of a measurement of expression of AR in epithelial and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei, and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area. In some embodiments, the morphometric information is based on image analysis of tissue subject to multiplex immunofluorescence and may include characteristic(s) of a minimum spanning tree (MST) and/or a fractal dimension observed in the images.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts whether a patient is likely to have a favorable pathological stage of prostate cancer, where the model is based on features including one or more (e.g., all) of preoperative PSA, Gleason Score, a measurement of expression of androgen receptor (AR) in epithelial and stromal nuclei and/or a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units, and a morphometric measurement of area of epithelial nuclei distributed away from gland units. In some embodiments, quantitative measurements of protein expression in cell lines are utilized to objectively assess assay (e.g.

Abstract: Systems and methods for analyzing vessels in multiplexed images include detecting large vessels using a spoke feature detection method, detecting long and narrow vessels using a line feature detection method, detecting smaller vessels using rolling-ball filtering and binary image operations to generate a mask, and evaluating any contour polygons resulting from these operations using quality measurements and other thresholds. Maturity determination and nuclei detection are also performed, resulting in an output of vessel characteristics and co-locations enabling enhanced analysis of multispectral images.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts whether a patient is likely to have a favorable pathological stage of prostate cancer, where the model is based on features including one or more (e.g., all) of preoperative PSA, Gleason Score, a measurement of expression of androgen receptor (AR) in epithelial and stromal nuclei and/or a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units, and a morphometric measurement of area of epithelial nuclei distributed away from gland units. In some embodiments, quantitative measurements of protein expression in cell lines are utilized to objectively assess assay (e.g.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.

Abstract: Embodiments of systems, methods, and apparatuses for thread selection and reservation station binding are disclosed. In an embodiment, an apparatus includes allocation hardware including reservation station binding logic to bind an operation to one of a plurality of reservation stations. In an embodiment, an apparatus includes thread selection logic to select a thread to be processed by a pipeline stage, wherein the thread selection logic to evaluate a plurality of conditions to select a thread, wherein the conditions include if a thread is active, if a thread has operations in an instruction queue, if a thread has available resources, and if a thread has no known stall.

Abstract: In general, one aspect of the subject matter described in this specification can be embodied in methods for assessing risk associated with prostate cancer, the methods including the actions of receiving patient data, comparing, with a processor executing code, the patient data to one or more predictive models, the one or more predictive models comprising at least one of (a) a disease progression (DP) model, the DP model being configured to predicts a likelihood of developing significant disease progression, and (b) a favorable pathology (FP) model, the FP model being configured to predict a likelihood of having organ confined, low grade disease in a prostatectomy, and outputting one or more results of the comparison Other embodiments of the various aspects include corresponding systems, apparatus, and computer program products.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.