548 results about "Image measurement" patented technology

The invention discloses a multi-target and long-distance field domain temperature measurement method based on dual-spectrum imaging. A visible light camera module and an infrared camera module are included. Obtaining internal parameters and external parameters in the visible light camera module and the infrared camera module, and optimizing the internal parameters and the external parameters; performing quick image feature search and image feature stereo matching on the acquired visible light image and infrared image to realize identification and positioning during image measurement; registering and fusing the visible light image and the infrared image by adopting a double-spectrum image fusion algorithm to obtain a fused image; carrying out image intersection measurement positioning and temperature measurement area stereo matching on the image; performing systematic edge calculation on the image by adopting a data-based intelligent analysis algorithm, and analyzing a temperature change trend according to the obtained image data to obtain the temperature of the measured object; the current running state of the detected power equipment is evaluated, the equipment fault is diagnosed, and the application end is used for storing, displaying and processing the detection result; and the temperature detection accuracy of the power equipment is effectively improved.

The invention discloses a high-precision particle image velocity measurement method, and relates to the technical field of particle image velocity measurement, and the method specifically comprises the steps: 1, building a high-precision particle image measurement experiment platform, capturing continuous particle images through a laser-camera system with a synchronous time sequence, achieving the precise synchronization of laser pulses and camera exposure through an FPGA synchronous controller, and carrying out the measurement of the continuous particle images; the method comprises the following steps of: 1, acquiring a displacement image captured by a high-speed camera, and verifying synchronization precision, 2, processing the displacement image captured by the high-speed camera by using a technology combining a cross-correlation method and an optical flow method, and 3, introducing singular value decomposition in a PIV data processing process, decomposing flow field data, and separating main signals and noise. The sub-pixel-level precision of particle displacement measurement is remarkably improved, the signal-to-noise ratio of data is enhanced, and real-time error correction is achieved.

The invention belongs to the field of quality detection of mobile automobile windshields, and discloses a quality detection method of a head-up display windshield based on machine vision, which comprises the following steps: acquiring an original image of an original projection virtual image formed by a standard image projected by a head-up display system through the windshield, and carrying out graying processing on the original image to obtain a gray image; a corresponding grey-scale map is obtained; extracting an ROI (Region of Interest) area, namely a virtual image area, from the grey-scale map, performing dual-threshold processing on the image from which the virtual image area is extracted so as to segment a background area and the virtual image area, highlighting edge features of a virtual image in the background area and the virtual image area, and obtaining a thresholding image; and measuring each physical parameter of the thresholding image, comparing the difference between the measurement result and the corresponding parameter of the standard image, and if the difference is within a preset threshold range, determining that the imaging quality of the head-up display windshield is qualified, otherwise, determining that the imaging quality of the head-up display windshield is unqualified. The stability and efficiency of HUD imaging quality measurement of the windshield are improved, and meanwhile the cost of the whole detection system is greatly reduced.

The invention discloses an image measurement method for precise size measurement. The method comprises the following steps: step 1, selecting a laser scanner and an optical image measurement instrument to form a measurement array according to geometrical characteristics of a workpiece; 2, calibrating and verifying the measurement array, obtaining a basic error curve of the equipment through a standard gauge block, and collecting real-time environmental parameters after verification is passed; 3, calculating an environment interference coefficient Kenv, and starting measurement at the moment; 4, monitoring equipment acceleration sensor data in real time, and generating an equipment stability index Si; 5, when Si is larger than S < safety >, measurement is executed, and a result is output; and step 6, carrying out consistency analysis on multi-device results, if the results are consistent, outputting a final value, otherwise, triggering dynamic re-calibration. According to the invention, multi-dimensional cooperative control can be realized, the precision bottleneck of traditional image measurement in a dynamic environment is broken through, and the method is suitable for precision manufacturing scenes with high requirements on measurement stability and reliability.

The invention discloses a cutter state real-time monitoring and compensating method, system and equipment and a medium, and relates to numerical control precision machining. In the method, a cutting edge optical image, an acoustic emission signal time domain waveform, a vibration acceleration parameter and real-time temperature data of a cutting area of a cutter in the machining process are collected; measuring the maximum width and depth of a wear belt through an image to form a wear characteristic quantized value, and judging a wear over-limit state; judging the damage state based on the continuous ultralimit time of the instantaneous mutation rate of the acoustic emission signal; judging the abnormal vibration grade and state through vibration spectrum analysis; and inputting the vibration spectrum and the temperature data into a prediction model to obtain a position offset prediction quantity. And calculating a size deviation value according to a wear / damage state, calculating a coordinate offset according to vibration abnormity, generating a cutter geometric compensation instruction or a motion trail compensation instruction, and completing real-time compensation operation. According to the scheme, the fine abnormal change of the cutter in the machining process can be captured in time, and compensation is conducted according to the fine abnormal change.

The invention discloses a method for quantitatively evaluating the CMAS corrosion resistance of a thermal barrier coating, which comprises the following steps: uniformly coating CMAS on the surface of the thermal barrier coating, and carrying out corrosion treatment according to set temperature and time; the corroded thermal barrier coating is subjected to longitudinal linear cutting, and the cut section is gradually ground and polished; sEM characterization is conducted on the polished cutting section, and an SEM image is shot for further quantitative analysis; based on the obtained SEM image, the corrosion depth of the CMAS in the thermal barrier coating is measured; selecting at least one identification area in the CMAS corrosion area, and calculating the area of the CMAS phase in each identification area; and calculating the corrosion degree C of the CMAS to the thermal barrier coating based on the proportion of the CMAS phase area in the identification area. The method is simple and easy to operate, the proportion of the area corroded by the CMAS in the corrosion area is introduced as a key evaluation index on the basis of corrosion depth measurement, and a unified, reliable and quantifiable standard is provided for objectively and quantitatively evaluating the CMAS corrosion resistance of the thermal barrier coating.

Disclosed is an imaging measurement device including a light source unit that emits first light and second light to a target, a capturing unit that detects a first active signal, which is reflected from the target based on the first light, and a second active signal, which is reflected from the target based on the second light, and obtains an active image based on the first active signal, a data processing unit that calculates a distance to the target based on the first active signal and the second active signal, and an image unit that obtains a three-dimensional (3D) image based on the active image and the calculated distance, and displays the 3D image.

The invention discloses a large-aperture plate glass stress birefringence surface imaging measurement method, belongs to the technical field of optical measurement, and aims to solve the technical problem of low glass stress birefringence measurement efficiency in the prior art. Comprising the following steps: moving a sample to be measured and a 1 / 4 wave plate out of a measuring light path, rotating a polarizer to find an extinction position, and rotating the polarizer by N angles nearby to obtain an angle # imgabs0 #; keeping the polarizer and the analyzer unchanged, moving the 1 / 4 wave plate into a measurement light path, rotating the 1 / 4 wave plate, and finding an extinction position; rotating the polarizer by N angles near the extinction position to obtain an angle # imgabs 1 #; the positions and the directions of the 1 / 4 wave plate and the polarization analyzer are kept unchanged, and the sample to be measured is moved into a measuring light path between the polarizer and the 1 / 4 wave plate; the polarizer is rotated through the polarization rotating mechanism, when the included angles between the polarizer and the x axis of the reference coordinate system are 0 degree, 60 degrees and 120 degrees respectively, the light intensities of the three images are obtained through the CCD camera, and the stress birefringence of the sample to be measured is obtained according to the three light intensities.

The present disclosure relates to techniques for fusing deep learning-based image reconstructions with noisy image measurements with provable assurances that the resulting improved image does not remove the information content of the original noisy measurements or image. Particularly, aspects are directed to obtaining measurement data from an imaging modality, generating a base image by solving an optimization problem using at least a signal model and the measurement data, generating, using a deep-learning model, a predicted image based on the measurement data, selecting a modified operator based on the signal model, generating an enhanced image by solving the modified optimization problem using at least: (i) the base image or the measurement data, (ii) the signal model, (iii) the predicted image, and (iv) the modified operator, and outputting the enhanced image.

The invention discloses an image processing and measuring method and system based on unmanned aerial vehicle radar and oblique photography, relates to the technical field of oblique photography image measurement, and is used for solving the problem that the accuracy of region division and anomaly detection results is reduced. The method comprises the following steps: calculating a vegetation change gradient in combination with a radar echo amplitude to generate vegetation distribution characteristics; extracting an under-forest ground and generating uniform extrapolation points; arranging a clinometer to obtain an elevation and a coordinate; calculating a local slope and a crown fluctuation amplitude; according to the method, the area vegetation coverage state is evaluated, abnormal areas are screened, extrapolation ground points of the abnormal areas are marked and output, high-precision exploration of the forest area is achieved, terrain complexity and vegetation distribution characteristics are accurately reflected, reliable data support is provided for forest management and terrain analysis, and exploration efficiency and precision are improved.

The invention relates to the technical field of migration measurement, in particular to an image processing measurement system based on edge calculation. The system comprises a target image real-time acquisition module, a target object feature measurement module, a before-migration and after-migration similarity measurement module and a before-migration and after-migration difference measurement module, and can perform image real-time acquisition and target object feature measurement by arranging edge computing nodes beside image acquisition equipment corresponding to a target area; obtaining corresponding target object image measurement features before style migration; obtaining corresponding target object reference image data in the target area, and carrying out image style migration and similarity measurement before and after style migration to obtain feature similarity corresponding to the target object image before and after style migration; and performing style migration difference measurement based on the feature similarity before and after the style migration corresponding to the target object image to obtain the difference degree before and after the style migration corresponding to the target object image. According to the invention, accurate measurement of the image style migration effect of the target object can be realized.

The invention belongs to the technical field of high-temperature flow field velocity testing, and discloses a PIV (particle image velocimetry) endoscopic protection device for measuring a high-temperature airflow velocity field, which is suitable for measuring three-dimensional velocity field distribution in a turbine channel, between stages and at an inlet and an outlet of a turbine in a high-temperature and high-speed airflow environment. The device is characterized by comprising a shell, an inner wall, a sapphire glass tube, a partition plate, a light guide window, a water inlet channel, a water outlet channel, an optical element, a mounting seat and a cavity. The shell, the inner wall and the sapphire glass tube are coaxially sleeved and respectively form two-stage interlayers; the space between the shell and the inner wall is divided into an n-shaped water inlet channel and an n-shaped water outlet channel through a partition plate, circulating flowing of cooling water is achieved, and an endoscope optical assembly and a sapphire glass tube are efficiently cooled. Light guide windows are formed in the side wall of the shell from top to bottom in an equal-diameter and equal-interval mode, and an optical element capable of moving up and down in the glass tube in the axial direction is combined, so that the narrow measurement section in the turbine can be accurately measured; according to the structure, the temperature near the sapphire glass tube can be controlled below 500K under the extreme condition that the external environment temperature is up to 2000K, high temperature is effectively isolated, thermal stress concentration is relieved, and stable signal transmission and imaging measurement are ensured. Compared with the prior art, the endoscope probe can accurately reach a measurement area which is difficult to cover by a traditional light source, and efficient and stable measurement of a high-temperature, complex and narrow space flow field is achieved.

Embodiments of the present disclosure may include a method for processing a spectrum image measurement, the method including receiving a spectrum image measurement. In some embodiments, the spectrum image measurement may include a plurality of power-frequency data values as a function of time and time data. Embodiments may also include selecting a prediction result based at least in part on the time data and an uncertainty model. Embodiments may also include generating a residual error image by applying the prediction result to the power-frequency data. Embodiments may also include scanning the residual error image for an anomaly. In some embodiments, an anomaly may be based at least in part on a portion of the residual error image exceeding a threshold range between a prediction result value and the power-frequency measured data value.

The invention discloses a marker-assisted visual positioning method and system for assisting cooperative management and control of a smart tunnel. The method comprises the following steps: acquiring an image; measuring a marker in the image and calculating a coordinate system transformation matrix; and based on the coordinate system transformation matrix, carrying out spatial positioning on the target vehicle in the image. The system comprises an image acquisition module, a matrix calculation module and a positioning module. According to the invention, space positioning can be realized at a low cost in a scene with poor signals. The method can be widely applied to the field of space positioning.

The present disclosure relates to an artificial intelligence-based load and heavy equipment collision prevention device and a control method thereof, the device including: a camera for capturing a forward image; a communication module for transmitting and receiving data to and from an external device; a memory in which at least one process for the artificial intelligence-based load and heavy equipment collision prevention is stored; and a processor for performing an operation according to the process. The processor can extract a person image and a dangerous object image, including the load and the heavy equipment, from the image using an artificial intelligence model, measure the separation distance between the extracted dangerous object image and the extracted person image, identify a collision risk on the basis of the measured separation distance, and output a warning message when the identified collision risk is present.

The invention discloses a knee arthritis image measurement model system and method based on deep learning, particularly relates to the technical field of image processing, and is used for solving the problem of low image measurement accuracy. According to the method, the image preprocessing technology and the deep learning segmentation method are integrated, high-precision automatic segmentation and analysis are performed on the knee joint image, the contrast ratio and the resolution ratio of the image are enhanced, meanwhile, the image quality is further improved through biased field correction and non-local mean value noise reduction, and the image segmentation is performed by adopting the U-Net model, so that the image quality is improved. A complex structure in the joint is effectively recognized, segmentation precision is improved, a segmentation strategy is dynamically adjusted according to measurement influence information generated in the segmentation process, the processing flow is optimized in real time through different regulation and control signals, diagnosis efficiency and accuracy are improved, and therefore the automation level and reliability of medical image processing are improved, and the medical image processing efficiency is improved. Efficient and accurate support is provided for clinic, and the accuracy of osteoarthritis image measurement is improved.

To provide an image measuring apparatus that can reduce the work conventionally required in image measurement.SOLUTION: An image measuring apparatus comprises: a CAD data storage section that stores CAD data of an article and CAD data information including design dimensions extracted from the CAD data, measurement points corresponding to the design dimensions, and edge detection tool conditions used to detect edges of the measurement points in advance for each different CAD data; a CAD data retrieval section that retrieves, from the CAD data storage section, the CAD data in which the shape of the article is similar to that of a measurement object represented in a captured image; a CAD data setting section that causes the CAD data identified on the basis of the retrieval to fit best to the image of the measurement object as the CAD data of the measurement object and sets the coordinate system of the CAD data which has been fitted best as a measurement coordinate system; and a measurement performing section that performs edge detection and dimensional measurement for each measurement point using the CAD data information corresponding to the CAD data of the measurement object for the image of the measurement object.SELECTED DRAWING: Figure 3

The invention relates to the technical field of river flow monitoring, and discloses a river flow control method and system based on image measurement. The method comprises the following steps: setting a space calibration point through a range finder, establishing a coordinate system, collecting a river image and carrying out geometric correction, calculating a water surface flow velocity by using an optical flow algorithm, calculating a sectional area by combining a water level and riverbed data, calculating an instantaneous flow rate after converting the surface flow rate into a vertical average flow rate, and generating control information according to an ecological flow rate condition. And controlling the opening degree of the water gate, the angle of the guide plate and the submerged adjusting dam according to the control information. According to the method, continuous and accurate measurement and calculation of the monitored section flow are realized based on an image acquisition means, a control mechanism linked with an ecological water demand threshold value is established, and the measurement process is ensured to be completed under a non-contact and remote control condition, so that the method is used for automation, intellectualization and ecological adaptability of water flow control of a dam.

The invention relates to the technical field of artificial intelligence and traditional Chinese medicine diagnosis, in particular to a traditional Chinese medicine tongue diagnosis image intelligent analysis system based on deep learning, which comprises a tongue picture acquisition module, a tongue picture measurement module, a tongue picture comparison module, a tongue picture comprehensive analysis module, a health consultation module and a data management module. Accurate extraction and quantitative analysis of tongue picture color features are realized by constructing a color manifold space and introducing Riemannian metric tensor and geodesic distance calculation; performing dynamic evolution tracking on tongue image change by adopting a thermal equation and a curvature flow model on a manifold; based on the geodesic distance, constructing a mapping relation between color features and syndromes, and generating syndrome probability distribution; meanwhile, tongue images collected at different times are compared and analyzed, the treatment effect is evaluated, the system is further combined with a traditional Chinese medicine knowledge graph, syndrome diagnosis, disease interpretation and dialectical treatment suggestions are provided, and the limitation that traditional tongue diagnosis is high in subjectivity and lacks quantitative standards is broken through.

The invention provides a method for measuring a roll angle of a vehicle through an image suitable for a structured pavement condition, and aims to compensate for accumulative errors and vibration influences of low-cost IMU measurement. According to the method, firstly, the geometric distance between laser beams is measured through an improved image processing method, and then high-precision roll angle measurement is achieved based on a regression function. In order to further improve the measurement accuracy, the collected laser image is input into the improved MobileNetV4 model, and the feature extraction and dynamic prediction capabilities are optimized through the technologies of multi-scale convolution, adaptive convolution kernel, dynamic feature selection and weighting and the like, so that the prediction of the roll angle of the vehicle is realized. The two methods are combined, a weighted average fusion mechanism is used, the weight is dynamically adjusted, and the precision and stability of inclination angle measurement are further improved. According to the method, high precision can be kept under the structured pavement condition, and compared with a low-cost IMU sensor measurement method, the method has good stability and real-time performance. The research provides a new means for the monitoring of the dynamic behaviors of the vehicle, and is of great significance to the development of vehicle safety and driving assistance systems.

The invention relates to a digital twin construction method and system for evolution analysis of a scouring pit in a near-dam region, and the method is characterized by comprising the following steps: firstly, obtaining multi-source heterogeneous data, and obtaining land-water integrated high-precision geographic space data through unmanned plane multi-view image measurement, laser radar scanning and single / multi-beam sounding technologies; the method comprises the following steps: firstly, constructing a dynamic digital twinborn model to provide a comprehensive data source for the twinborn model, secondly, constructing a dynamic digital twinborn model to realize real-time synchronization of a physical world and a digital world, secondly, carrying out evolution analysis, accurate prediction and decision optimization on a near-dam-area scour pit, and finally, carrying out calculation optimization and real-time display on a near-dam-area twinborn body. The erosion pit evolution process and early warning information are dynamically displayed through the three-dimensional visualization platform, the algorithm is reasonable, real-time synchronization of the physical world and the digital world is achieved, the monitoring precision, the analysis efficiency and the prediction precision of the near-dam-area erosion pit are greatly improved, and the method is suitable for popularization and application. And intelligent decision support is provided for safe operation of the hydro-junction.

The invention discloses a curvature compensation type metal material geometric dimension image measurement method and system, and relates to the technical field of dimension measurement. The curvature compensation type metal material geometric dimension image measurement method comprises the following steps: A1, sample dimension identification and outer contour test; a2, calculating and correcting the cross section area; a3, establishing a correlation model by considering influence factors; a laser measurement light curtain and a displacement sensor are combined to realize synchronous high-precision acquisition of the contour, the thickness and the length; a curvature compensation image algorithm is used for correcting measurement errors caused by curvature characteristics, and the measurement precision is improved; dimensional deviation, shape deviation and parallel section thickness and length verification are integrated, and it is ensured that the detection result is comprehensive and reliable; different sample expansion conditions caused by environmental factors and material factors are considered, a relation model is established, the sample expansion conditions can be directly predicted according to the environmental factors and the material factors, and then sample parameters are calculated more accurately; the whole process does not need manual intervention.

The invention belongs to the technical field of oil production engineering, and provides a method for identifying proppant particles based on ResNet-KAN. The identification method comprises the following steps: acquiring logging rock debris samples at different well depths in a drilling and coring process; screening and photographing the single particles of the logging rock debris sample; extracting an image of the single particle, measuring the particle size of the single particle, and storing; making a training set and a verification set of the model; a ResNet-KAN residual error neural network model is constructed; training the model by using a training set, and verifying by using a verification set; and identifying the image of the single particle by using the trained model so as to identify the proppant particles. According to the method, the KAN network is used for replacing a linear full connection layer of a traditional ResNet network, so that further optimization of the ResNet network is achieved, and the method has the advantage that the propping agent particles in the coring well logging rock debris in the hydraulic fracturing test field can be automatically, rapidly and accurately recognized.

The invention relates to the technical field of computer vision and image measurement, and discloses a binocular camera synchronous automatic calibration system and a calibration method. The inner ring flange plate is fixed on the base and is used for fixing M calibration plates; the outer ring flange plate is arranged on the base, rotates around the radius tangential direction of the inner ring flange plate and is used for arranging and driving N groups of binocular cameras; the cross-shaped sliding table assembly is arranged on the inner ring flange plate and is used for driving the calibration plate to carry out position transformation; the camera bracket is fixed on the outer ring flange plate and is used for fixing a binocular camera; the control and data processing unit is connected with the outer ring flange plate, the cross-shaped sliding table assembly and the binocular camera and used for controlling the outer ring flange plate to rotate and controlling the calibration plate to move, and the binocular camera collects images and then completes calibration. According to the invention, automatic acquisition of multiple groups of images with different poses can be completed in one rotation period, full-automatic calibration of multiple groups of binocular cameras is realized, and the production efficiency is improved.

The invention relates to the technical field of workpiece alignment, in particular to a machined workpiece automatic alignment method and system based on image measurement, and the method comprises the following steps: collecting a workpiece image, analyzing a local curvature change rate, adjusting sampling density, reconstructing surface features, generating micro-topography data, calculating a stability score, and outputting an attitude correction parameter. And tracking a time sequence deviation derivation instruction response deviation track, fitting a deviation curve to invert delay mapping to generate an error correction table, and mapping a control signal to adjust a step length to generate an adaptive driving instruction. According to the method, the morphological stability score is calculated through the ratio of the boundary curvature continuity to the area compactness of the equal-optical-density region, accurate judgment on the boundary contour under different image conditions is achieved, the response offset function is constructed with the help of the least square method, the execution error correction table is mapped, the response precision and execution consistency of the alignment instruction are improved, and the accuracy of the alignment instruction is improved. And the alignment efficiency and the posture stability of the workpiece under the complex morphology condition are improved.

To provide a method and a system for precisely aligning chiplets with bonding sites.SOLUTION: A bonding system for aligning chiplets 22 to a substrate 25 includes acquiring an image of an area on the chiplet with an alignment microscope 145 or an upward microscope 141, measuring a deviation from planarity of the area on the chiplet, estimating a chiplet position error of the chiplet on the basis of at least the image of the area and the deviation from planarity of the area, and adjusting a relative position of the chiplet to the substrate based on the chiplet position error.SELECTED DRAWING: Figure 1

The invention discloses an RTK image mismatching point detection method, a storage medium and an RTK image mismatching point detection device, and relates to the technical field of RTK image measurement, and the technical scheme is characterized in that the method comprises the following steps: carrying out the preliminary matching of feature points, keeping the feature points smaller than a threshold T in the preliminarily matched feature points, and taking the rest as mismatching points; judging whether the camera posture change is smaller than a threshold T; calculating the position increment of the reserved feature points on the image; calculating the motion direction and the motion distance of each reserved feature point on the image according to the position increment; calculating the mean value and the standard deviation of the motion direction and the motion distance of the reserved feature points on the image; the consistency between the motion direction and the motion distance of each feature point and the mean value is judged; and detecting and eliminating mismatching points in the reserved feature points by using an RANSAC (Random Sample Consensus) algorithm. According to the method, the principle that the motion direction and the motion distance of the feature points in the adjacent images are consistent is utilized, mismatching points are detected and eliminated, and the measurement precision of the images is improved.

The invention provides a three-dimensional mining-induced stress monitoring device and method based on optical micrometer micro-deformation, and belongs to the technical field of underground coal mine engineering mining-induced stress testing. The device comprises a speckle field image monitoring module, an image acquisition module and a data storage and transmission module; the speckle field module is used for providing a speckle field and forming a speckle field change image; the image acquisition module is used for acquiring a speckle field change image of one circle of the inner wall of the first section of circular ring shell under the irradiation of the light source; and the data storage and transmission module is used for storing and transmitting the speckle field image. The device is based on the optical measurement micro-deformation technology, speckle strain field change images on the periphery of the inner wall of the device shell are monitored through the miniature industrial camera, the measurement precision can reach the sub-pixel level, and in the high-temperature, high-pressure and high-ground-stress complex deep coal mine environment, the monitoring result can be stably and precisely output in real time.

A microscope based system for image-guided microscopic illumination is provided. The system may include a microscope, a stage, an imaging subsystem adapted to obtain an image of a sample on the stage, a processing subsystem adapted to identify regions of interest in the sample from images obtained by the imaging subsystem, and a pattern illumination subsystem adapted to illuminate the regions of interest based on coordinates derived from the images by the processing subsystem. Methods of calibrating the microscope based system may include projecting light from the pattern illumination subsystem onto the sample in the illumination pattern based on computed coordinates of the desired pattern, obtaining an image of the illumination pattern from the sample with the imaging subsystem, measuring differences between actual coordinates of the illumination pattern in the image and the computed coordinates, ‘and generating correction factors based on the measured differences to calibrate the system automatically.

Systems and methods for reconstructing medical images based on the trained deep learning processes, and for training deep learning processes, are disclosed. In some examples, image measurement data is received. A histo-image is generated based on the image measurement data. Further, an attenuation map, such as a μ-map, is received. An attenuation histo-image is generated based on the attenuation map. Further, a trained machine learning process, such as a trained neural network, is applied to features generated from the histo-image and the attenuation histo-image. Based on the application of the machine learning process to the histo-image and the attenuation histo-image, output image data characterizing an image volume is generated. In some examples, a machine learning process is trained based on histo-images and corresponding attenuation histo-images. The trained machine learning process may be employed to reconstruct images, such as positron emission tomography (PET) images.