Abstract: In an approach for constructing an ensemble model from a set of base learners, a processor performs a plurality of boosting iterations, where: at each boosting iteration of the plurality of boosting iterations, a base learner is selected at random from a set of base learners, according to a sampling probability distribution of the set of base learners, and trained according to a training dataset; and the sampling probability distribution is altered: (i) after selecting a first base learner at a first boosting iteration of the plurality of boosting iterations and (ii) prior to selecting a second base learner at a final boosting iteration of the plurality of boosting iterations. A processor constructs an ensemble model based on base learners selected and trained during the plurality of boosting iterations.

Abstract: An augmented reality-based horticultural care tracking system to collect information about plants on a per plant or near per plant basis in order to identify issues and generate itineraries that include task lists for remedial courses of actions is disclosed. A network-enabled augmented reality device can be employed by operators of various growing operations in order to overlay digital information such as tasks, images, and related information in a real-time environment. The augmented reality device can communicate with administrative personnel at an operating station and/or intermediate servers in the network in order to send and receive status updates and notifications to properly execute the tasks in the itinerary and evaluate the courses of actions' efficacy.

Abstract: Virtual tools are used to manipulate aspects of a three-dimensional medical image volume. The virtual tools are registered with the image volume. Presentation of the image volume is manipulated by an image processor in response to use of the virtual tools. The virtual tools may be used to facilitate analysis of the image volume.

Abstract: Provided herein are methods of estimating subject-specific parameters of growth dynamics of a cancer tumor in a subject having cancer. The methods can be used to personalize treatment protocols for a subject, stage the given disease in the subject, measure response to therapy, phenotype for patient selection to participate in drug trials, measure stability of an anatomical structure, or predict rate of change of the given disease. Also provided are methods of predicting growth dynamics of a cancer tumor, and computer systems and computer-implemented methods for estimating subject-specific parameters of growth dynamics of a cancer tumor in a subject having cancer.

Abstract: According to one embodiment, a radiotherapy support apparatus has processing circuitry. The processing circuitry obtains an activity level distribution representing radiation resistance in a tumor area of a subject, and produces a first treatment plan in which a radiation administered dose to the tumor area changes within the tumor area in accordance with the activity level distribution.

Abstract: Embodiments of the present disclosure relate generally to mobile computing technology and, more particularly, but not by way of limitation, to systems for generating and presenting a graphical user interface (GUI) that includes a presentation of an animated icon (e.g., a digital pet) on a display of a client device.

Abstract: Systems and methods for generating an integrated circuit (IC) chip design are described. One of the methods includes receiving, on a data sheet, by a server, electrical parameters of a system on chip (SoC) to be designed. The method further includes receiving physical parameters of the SoC on the data sheet, generating a first design of the SoC according to the electrical parameters and the physical parameters, and receiving test parameters for testing the first design. The method further includes testing, via a design verification tool, the first design by applying the test parameters to the first design, receiving a second design of a second SoC, and coupling the second design to the first design to generate a first IC chip design. The method includes arranging the first IC chip design to be included on a shuttle for fabricating a first IC chip.

Abstract: The risk analysis system according to the present invention includes: a storage apparatus which stores subject data including information related to health of a subject; an analyzer which analyzes a risk related to the health of the subject based on the subject data acquired from the storage apparatus; and an output apparatus which outputs an analysis result by the analyzer. The analyzer has: a risk estimating unit which estimates an event onset risk of the subject based on the subject data; and a medical expense predicting unit which predicts future medical expenses, which are medical expenses to be incurred in the future by the subject, based on the event onset risk estimated by the risk estimating unit and the subject data.

Abstract: The risk analysis system according to the present invention includes: a storage apparatus which stores subject data including information related to health of a subject; an analyzer which analyzes a risk related to the health of the subject based on the subject data acquired from the storage apparatus; and an output apparatus which outputs an analysis result by the analyzer. The analyzer has: a risk estimating unit which estimates an event onset risk of the subject based on the subject data; and a medical expense predicting unit which predicts future medical expenses, which are medical expenses to be incurred in the future by the subject, based on the event onset risk estimated by the risk estimating unit and the subject data.

Abstract: A compliance and effectiveness tracking engine system including a sensor system to obtain sensed sleep data for a sleep session for a user, and a user interface implementing a user data acquisition system to obtain perceived sleep data from the user after the sleep session. The system further includes a server system implementing a predictive engine to predicted sleep data for the user, based on user background data and transactional data reflecting one or more medical interventions for the user. The server implementing a compliance and effectiveness tracking engine (CETE) to compare the sensed sleep data, the perceived sleep data, and the predicted sleep data, and to determine effectiveness of the one or more medical interventions for the user, and compliance with a protocol associated with the one or more medical interventions.

Abstract: A method of predicting a gene target sequence for a gene-modifying therapeutic, such as a CRISPR-based therapeutic, that includes the steps of determining a genomic dataset for one or more infectious bacterial samples isolated from one or more hospitals, and inputting the genomic dataset for the one or more infectious bacterial samples into a machine learning model to determine the presence of antimicrobial resistance genes.

Abstract: The disclosure presents a new computer based model framework to predict drug effects over multiple time and spatial scales from the drug chemistry to the cardiac rhythm. The disclosure presents a new computer based model framework to predict drug effects from the level of the receptor interaction to the cardiac rhythm.

Abstract: Method and system including displaying a first representation of a medication treatment parameter profile, displaying a first representation of a physiological profile associated with the medication treatment parameter profile, detecting a modification to a segment of the medication treatment parameter profile, displaying a modified representation of the medication treatment parameter profile and the physiological profile based on the detected modification to the segment of the medication treatment parameter profile, modifying an attribute of the first representation of the medication treatment parameter profile, and modifying an attribute of the first representation of the physiological profile are provided.

Abstract: An apparatus and method for scalable qubit addressing. For example, one embodiment of a processor comprises: a decoder comprising quantum instruction decode circuitry to decode quantum instructions to generate quantum microoperations (uops) and non-quantum decode circuitry to decode non-quantum instructions to generate non-quantum uops; execution circuitry comprising: an address generation unit (AGU) to generate a system memory address responsive to execution of one or more of the non-quantum uops; and quantum index generation circuitry to generate quantum index values responsive to execution of one or more of the quantum uops, each quantum index value uniquely identifying a quantum bit (qubit) in a quantum processor; wherein to generate a first quantum index value for a first quantum uop, the quantum index generation circuitry is to read the first quantum index value from a first architectural register identified by the first quantum uop.

Abstract: Improved computer-implemented tools for use in modeling/simulating spatial charge distributions for electrophysiological systems are provided. The improvements are in three areas: (1) the use of solid angles to calculate quantities of free charge and/or bound charge in calculation cells and/or the movement of quantities of free charge across one or more faces of a calculation cell; (2) the use of flattened calculations cells having only two faces with substantial areas as seen from the free charge and/or the bound charge of the electrophysiological system; and (3) the use of at least two spatial charge distributions, specifically, at least one for bound charge and at least one for free charge, so as to include the effects of relative dielectric constants greater than 1.0 for part or all of an electrophysiological system. The three improvements can be used individually or in combinations.

Abstract: Systems, methods and apparatus related to a self-preservation/self-protection system (SPS). The SPS system includes a local area situation awareness sensor suite (LASASS), multiple central pattern generator (mCPG) decision circuitries and related actuators. The SPS system utilizes the LASASS, mCPG circuitries and actuators to perform the desired processing and effectuate changes in the position of an object to be detected or avoided.

Abstract: Disclosed herein are methods, systems, and processes to detect valid clusters and eliminate spurious clusters in cybersecurity-based computing environments. A cluster detection and elimination model is trained by accessing a dataset with raw data that includes data points associated with computing devices in a network and applying two or more different clustering methodologies independently to the dataset. The resulting cluster detection and elimination model is used to compare two or more clusters to determine whether a cluster from one clustering methodology matches another cluster from another clustering methodology based on centroid locations and shared data points.

Abstract: Systems and methods are disclosed for receiving a target electronic image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning system to the target electronic image to identify a region of interest of the target specimen and determine an expression level of, category of, and/or presence of a biomarker in the region of interest, the biomarker comprising at least one from among an epithelial growth factor receptor (EGFR) biomarker and/or a DNA mismatch repair (MMR) deficiency biomarker, the machine learning system having been generated by processing a plurality of training images to predict whether a region of interest is present in the target electronic image, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the determined expression level of, category of, and/or presence of the biomarker in the region of interest.

Abstract: A user interface for a beer recipe creator may have a series of icons that may represent ingredients. A user may drag and drop or otherwise add the icons to containers on a display screen to add or remove ingredients to the recipe. With each added or removed ingredient, a set of descriptors may be updated. The descriptors may include numerical values of beer parameters as well as textual descriptions and visual descriptions. The system may allow a user to start with a desired beer style, and the parameters may show variances from the selected style. The system may generate an ingredients list, as well as a brewing recipe that may be transferred to a controller for a beer making machine. The system may adjust certain parameters that are controllable by the beer making machine to make flavor and other adjustments selected by a user.

Abstract: A method of designing a molecule for an environment of interest using a quantum computer includes providing a linear superposition of a plurality of molecular species, the plurality of molecular species being initially weighted by equal initial coefficients; determining a lowest-energy quantum state for the superposition of the plurality of molecular species in a vacuum environment and in the environment of interest using a quantum optimization process; calculating a difference in lowest energy states between the vacuum environment and the environment of interest for each molecular species to provide a cost of the superposition of the plurality of molecular species; performing a quantum optimization process to determine a minimum cost for the superposition of the plurality of molecular species and to determine updated coefficients weighting the plurality of molecular species; and identifying the molecule for the environment of interest based on a comparison of the updated coefficients.

Abstract: Computer-implemented method and system for monitoring dental implant comprising the steps of graphically simulating an anatomy of a provided dental prosthesis coupleable to a dental implant; simulating an optimized implant site for the dental implant as a function of implant parameters of the dental implant and first parameters of the optimized implant site; calculating a plurality of optimal dental implants; selecting a usable implant from the plurality of optimal dental implants; calculating first deviations between first parameters of the optimized implant site and first parameters of the usable implant; calculating second deviations between second parameters of the optimal dental implants not selected as usable implants and first parameters of the optimized implant site; calculating real optimized parameters of the optimized implant site as a combined function of first deviations and second deviations.

Abstract: The systems and methods can accurately and efficiently determine a myocardial risk from a lesion disposed along a coronary segment using hemodynamic characteristic(s) associated with one or more sections of the corresponding lesion site. The method may include segmenting one or more lesion sites disposed along at least one arterial segment of the one or more arterial segments of the coronary model into one or more sections. Each lesion site includes a lesion. The method may include determining one or more characteristics for at least one section using at least the one or more characteristics associated with the at least one arterial segment. The one or more characteristics for the at least one section including hemodynamic force characteristic(s) (e.g., wall shear stress (WSS)). The method may include determining one or more risk indices for each lesion site using at least the hemodynamic force characteristic(s) for the at least one section.

Abstract: An automated measurement device and method for coronary artery disease scoring is disclosed. An example device includes a processor configured to obtain a computerized model of a plurality of vascular segments of a patient and create an unstenosed computerized model from the computerized model by virtually enlarging at least some locations of the vascular segments of the computerized model. The processor also determines vascular state scoring tool (“VSST”) scores based on characteristics of vascular locations along the vascular segments. The processor further determines a severity of stenosis for the vascular locations based on comparisons of first blood flow parameter values at the vascular locations in the computerized model to corresponding second blood flow parameter values at the same vascular locations in the unstenosed computerized model. A user interface of the device displays the severity of stenosis in conjunction with the VSST scores for the vascular locations.

Abstract: Methods and apparatus for planning and/or carrying out a total knee replacement surgical procedure on a knee of a leg of a patient are described. Anatomical data for the leg of the patient is obtained, which allows the femoral mechanical axis, the tibial mechanical axis and the joint line of the knee to be determined. A planned proximal tibial cut angle and a planned distal femoral cut angle are determined. A total knee replacement procedure is carried out on the knee of the patient, wherein a distal femoral cut is made using the planned distal femoral cut angle and a proximal tibial cut is made using the planned proximal tibial cut angle.

Abstract: In a method of molecular scaffold hopping an interface of a scheduler computer sends instructions, prepared by the scheduler computer, to a job runner computer to perform a plurality of separate computational tasks. Each of the separate computational tasks includes calculating one or more chemical properties for a query molecule or molecules in a library of molecules. One or more of the plurality of separate computational tasks performed on the job runner computer are preemptible computing instances. Status indicators sent from the job runner computer are received by the interface for each of the plurality of separate computational tasks. The indicators are one of: incomplete, completed, or failed computing instances. The interface resends the instructions to the job runner computer that correspond to the separate computational tasks having the failed computing instance indicator to increase fault-tolerance against the separate computational tasks not attaining the completed computing instance indicator.

Abstract: Disclosed herein are systems and methods for providing interactive graphical user interfaces (GUIs) for users, such as medical professionals, to glean insight about connectivity data associated with a particular brain. A method can include overlaying nodes representing locations of parcels of a patient's brain on a representation of a brain and displaying the representation of the brain with the overlaid nodes in a GUI. Nodes having connectivity above a first threshold can be represented in a first indicia and nodes having connectivity below a second threshold can be represented in a second indicia. The method can include receiving user input and taking an action based on the user input. The user input can include selecting an area of the representation of the brain for excision. Taking an action based on the input can include calculating an impact of excising the area of the brain on the particular patient.

Abstract: A system and method for analyzing a data store of de-identified patient data to generate one or more dynamic user interfaces usable to predict an expected response of a particular patient population or cohort when provided with a certain treatment. The automated analysis of patterns occurring in patient clinical, molecular, phenotypic, and response data, as facilitated by the various user interfaces, provides an efficient, intuitive way for clinicians to evaluate large data sets to aid in the potential discovery of insights of therapeutic significance.

Abstract: A method, a device and a security system for image data processing based on VR or AR are disclosed. In one aspect, an example image data processing method includes reconstructing, based on three-dimensional (3D) scanned data of a containing apparatus in which objects are contained, a 3D image of the containing apparatus and the objects contained in the containing apparatus. The reconstructed 3D image is stereoscopically displayed. Manipulation information is determined for at least one of the objects in the containing apparatus based on positioning information and action information of a user. At least a 3D image of the at least one object is reconstructed based on the determined manipulation information. The at least one reconstructed object is presented on the displayed 3D image.

Abstract: A method for vegetation restoration or rehabilitation of simulating a natural ecosystem based on machine learning (ML) includes: acquiring historical growth environment data of a vegetation community; extracting a site condition feature and a growth condition feature of each vegetation species; restoring and rehabilitating a vegetation community structure selection model; and selecting, based on the vegetation community structure selection model, an optimal vegetation species according to current growth environment data of the vegetation community, and restoring and rehabilitating a vegetation community simulating a natural ecosystem. The method comprehensively considers various factors affecting vegetation restoration based on the site condition and the growth condition.

Abstract: An example system includes an object and a support frame supporting the object. The support frame constrains movement of the object relative to the support frame, and the support frame includes at least one of a cage or a shackle to non-rigidly constrain movement of at least a part of the object.

Abstract: A method, executed at a controller for adapting a virtual object model, and a controller for executing the suggested method, where the method comprises acquiring of a virtual object model of a relevant virtual object and acquiring of at least one real object model of a relevant real object. Matching, according to at least one matching criteria, at least a part of the virtual object model to at least a part of one of the at least one real object model, selecting the best matching real object, and modifying at least a part of the virtual object model with respect to the at least part of the selected real object model.

Abstract: One embodiment of the present invention provides a computer implemented method for generating a training set to train a convolutional neural network comprising the steps of providing prediction space data to a General Logic Gate Module (GLGM). Prediction space expert judgement is also provided to the GLGM and to a sensitivity and importance module. The GLGM determines or outputs state possibilities. The state possibilities are provided to the sensitivity and importance module and to the feature extraction module. Feature extraction algorithms are applied to the state possibilities within the feature extraction module to produce a training possibility set that is a virtual training possibility set. The training possibility set is provided to a state inferential module and to a final training set.

Abstract: A system, methods, and apparatus are described to collect and prepare single cells and groups of cells from microsamples of specimens and encode spatial information of the physical position of the cells in the specimen. In some embodiment, beads or surfaces with oligonucleotides containing spatial barcodes are used to analyze DNA or RNA. The spatial barcodes allow the position of the cell to be defined and the nucleic acid sequencing information, such as target sequencing, whole genome, gene expression, used to analyze the cells in a microsample for cell type, expression pattern, DNA sequence, and other information, in the context of the cell's physical position in the specimen. In other embodiment, markers such as isotopes are added to a microsample to encode spatial position with mass spectoscopy or other analysis. The spatial encoded information is then readout by analysis such as DNA sequencing, mass spectrometry, fluorescence, or other methods.

Abstract: Provided is an apparatus for non-invasively estimating bio-information by analyzing a pulse waveform. The apparatus for estimating bio-information according to an aspect of the present disclosure includes a processor configured to obtain a first characteristic point from a first pulse wave signal measured by a pulse wave sensor at a calibration time, obtain a second characteristic point from a second pulse wave signal measured by the pulse wave sensor at a bio-information estimation time, based on time information of the obtained first characteristic point, and estimate the bio-information of an object based on the obtained second characteristic point.

Abstract: A method for optimal design of experiments for joint model selection and parametrization determination of a symbolic mathematical model includes: determining a prediction value for a given inquiry data point, functional form and parameterization for conducting an experiment relating to a system under investigation; assuming a set of input-output data pairs as a starting point in a model discovery process relating to the system under investigation; performing discovery of symbolic models minimizing complexity for a bounded misfit, or minimizing a misfit measure, subject to bounded complexity; determining a new data point through optimal experimental design that informs best as for the underlying symbolic models; and updating a posterior distribution, given results of the experiment relating to the system under investigation for the determined new data point to enable informed assessment among a plurality of functional forms and parameterizations. An apparatus configured to perform the method is also provided.

Abstract: The invention provides for a means of aligning a first virtual object with a second virtual object that is different from the first virtual object within a scene volume in a 3D virtual space. The method includes performing a 3D scan of the user's head to get the first virtual object. The second virtual object comprises a 3D model of a mask. The method further determining a location of a first surface point on a surface of the first virtual object based on a first ray casting of the first virtual object, and determining a location of a second surface point on a surface of the second virtual object based on a second ray casting of the second virtual object. The second surface point has a desired positional relationship with respect to the first surface point. The first ray casting originates from outside the scene volume and the second ray casting originates from inside the scene volume.

Abstract: Systems and methods are described for performing at least one of assessing, optimizing and/or controlling the performance of an Anaerobic Digestion (AD) plant. The system comprises a server that provides a user interface for allowing a user to enter user inputs to define various aspects of the AD plant operation and to view results of the simulation; a database for storing the inputs used for the simulation of the anaerobic digestion plant, the inputs including feedstock inputs, AD operational inputs, and simulation criteria; and a simulation engine that can be operated in an at least one of an off-line simulation mode for generating off-line simulator predictions, a near-line simulation mode for optimizing the performance of the system and an online mode for using machine learning to tune the performance of various models used in simulating the operation of the AD plant.

Abstract: A normal set of cells is characterized using flow cytometry. A centroid and radius are defined for a set of clusters in an n-dimensional space corresponding to a normal maturation for a cell lineage in the normal set of cells. A test set of cells is characterized using flow cytometry and the characterization is compared to the defined set of clusters. Support Vector Machine (SVM) subroutines are employed to identify reference populations of interest by generating multidimensional boundary definitions. These boundary definitions may be used to identify reference populations to use in defining or refining a centroid line or a radius or radii defining a set of normal clusters, and to characterize and compare a test set of cells to the defined set of normal clusters.

Abstract: Systems and methods for generating a 3D model of a dentition are disclosed herein. A method includes generating a first 3D model of a dentition including a plurality of model teeth. The method includes receiving at least one digital representation comprising patient teeth. The method includes determining a virtual camera parameter. The virtual camera parameter corresponds with a camera used to capture the digital representation. The method includes comparing, based on the virtual camera parameter, a first position of a model tooth with a position of a corresponding patient tooth of the digital representation. The method includes moving the model tooth from the first position to a second position. The second position is based on the position of the corresponding patient tooth. The method includes generating a second 3D model comprising the model tooth of the first 3D model in the second position.

Abstract: An automated method for determining a coagulation result of a biological sample is presented. The method includes obtaining a time series representing measurement data of a sample. The time series spans a period in which a clotting reaction is supposed to take place. The method includes obtaining a global model function configured to model measurement data of a sample in which a clotting reaction takes place. The global model function is configured to model the measurement data as a sigmoidal shape with at least one inflection point. The absolute value of the maximum curvature of the sigmoidal shape is larger on one side of the at least one inflection point than on the other side. The method includes fitting the model function to the time series representing measurement data to obtain a fitted model function and determining a coagulation result of the sample based on the fitted model function.

Abstract: An implant, a fitting plate suitable for placing of an implant, and a method for manufacturing an implant suitable for application on one or more bones.

Abstract: A method of generating a classifier includes a step of classifying each member of a development set of samples with a class label in a binary classification scheme with a first classifier; and generating a second classifier using a classifier development process with an input classifier development set being the members of the development set assigned one of the two class labels in the binary classification scheme by the first classifier. The second classifier stratifies the members of the set with an early label into two further sub-groups. We also describe identifying a plurality of different clinical sub-groups within the development set based on the clinical data and for each of the different clinical sub-groups, conducting a classifier generation process for each of the clinical sub-groups thereby generating clinical subgroup classifiers.

Abstract: A computer-implemented method for generating anatomical data associated with a musculoskeletal joint, the method comprising: receiving as input variation data representing change with time of a musculoskeletal joint of interest caused by a condition; receiving as input patient data representing the musculoskeletal joint of interest of a patient at a current time; and processing the variation data and the patient data to generate said anatomical data, wherein said anatomical data comprises data indicating the musculoskeletal joint of interest of the patient at a predetermined time different to the current time.

Abstract: The monitoring and control of bioprocesses is provided. The present disclosure provides the ability to generate generic calibration models, independent of cell line, using inline Raman probes to monitor changes in glucose, lactate, glutamate, ammonium, viable cell concentration (VCC), total cell concentration (TCC) and product concentration. Calibration models were developed from cell culture using two different CHOK1SV GS-KO™ cell lines producing different monoclonal antibodies (mAbs). Developed predictive models, qualified using an independent CHOK1SV GS-KO™ cell line not used in calibration, measured changes in glucose, lactate, ammonium, VCC, and TCC with minor prediction errors over the course of cell culture with minimal cell line dependence. The development of these generic models allows the application of spectroscopic PAT techniques in a clinical manufacturing environment, where processes are typically run once or twice in GMP manufacturing based on a common platform process.

Abstract: A system, method and program product for a mechanistic model search engine. A system is disclosed having: a search interface for receiving input including text and functions relating to mechanistic models; a source interface for crawling online sources for mechanistic model information, wherein the information sources include text, tables, graphs, and functions; a context analysis system that determines parameter-based details from text information; a parameter processing system that derives parameter-based details from functions; and a search algorithm that compares parameter-based details determined from the input against parameter-based details determined from the information sources to identify mechanistic model search results.

Abstract: A computer-implemented method for creating an activity-optimized cutting guides for surgical procedures includes receiving one or more pre-operative images depicting one or more anatomical joints of a patient, and creating a three-dimensional anatomical model of the one or more anatomical joints based on the one or more pre-operative images. One or more patient-specific anatomical measurements are determined based on the three-dimensional anatomical model. A statistical model of joint performance is applied to the patient-specific anatomical measurements to identify one or more cut angles for performing a surgical procedure. A patient-specific cutting guide is created that comprises one or more apertures positioned based on the one or more cut angles.

Abstract: A system and method for streamlining inventory and ordering for certain surgical supplies. The method includes scanning, by an imaging device, a surgical site and receiving, by a processor communicatively coupled to the imaging device, data from the scan. The method also includes the processor analyzing the data, where the analyzing includes searching the data to identify predefined key features in the data that are parameters utilized by a Statistical Shape Model (SSM). The processor applies the SSM to generate a three dimensional replica of a predetermined portion of the surgical site. The processor also defines, based on the replica, at last one of: surgical planes or orientations. The processor then utilizes the replica and the surgical planes or orientations to select a solution.

Abstract: A convolutional neural network predicts which regions of a tissue slice would be stained by a first stain by training a model to identify those regions based only on tissue stained by a second stain. Thereafter the first stain need not be used to mark cancerous regions on other tissue slices that are stained with the second stain. The training slice is stained with a first immunohistochemical stain and a second counterstain. A target region of an image of the training slice is identified using image analysis based on the first stain. A set of parameters for associated mathematical operations are optimized to train the model to classify pixels of the image as belonging to the target region based on the second stain but not on the first stain. The trained parameters are stored in a database and applied to other images of tissue not stained with the first stain.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: Emission imaging data are reconstructed to generate a low dose reconstructed image. Standardized uptake value (SUV) conversion (30) is applied to convert the low dose reconstructed image to a low dose SUV image. A neural network (46, 48) is applied to the low dose SUV image to generate an estimated full dose SUV image. Prior to applying the neural network the low dose reconstructed image or the low dose SUV image is filtered using a low pass filter (32). The neural network is trained on a set of training low dose SUV images and corresponding training full dose SUV images to transform the training low dose SUV images to match the corresponding training full dose SUV images, using a loss function having a mean square error loss component (34) and a loss component (36) that penalizes loss of image texture and/or a loss component (38) that promotes edge preservation.