Geometric Image Distortion Research Articles

SAR Image Classification Using Greedy Hierarchical Learning With Unsupervised Stacked CAEs

Synthetic aperture radar (SAR) can provide stable data source for earth observation due to its advantages of all day and night, all-weather, and strong penetration. SAR image classification as a fundamental procedure has been proved its great value in plenty of remote sensing applications. Conventional classification algorithms mainly rely on hand-designed features, which are susceptible to widespread coherent speckle noise and geometric distortion in high-resolution SAR images. Inspired by the recent impressive success in data mining and deep learning, a greedy hierarchical convolutional neural network (GHCNN) is developed. It aims at obtaining optimized feature representation, relieving the effect of speckle noise, and promoting the local pattern recognition of geometric distortion in single-polarized SAR image classification. First, a series of convolutional autoencoders (CAEs) is trained in the greedy layer-wise unsupervised strategy. This step provides an unbiased regularizer and <i>a priori</i> distribution derived from large volumes of unlabeled SAR patches. Then, to optimize multiple parameter subspaces globally, several CAEs are coupled together to form a deeper hierarchical structure in a stacked and unsupervised fashion. Afterward, a convolutional network with identical topology inherits the pretrained weights. After supervised finetuning, it realizes class prediction. Synchronously, t-distributed stochastic neighbor embedding (t-SNE) algorithm is applied to monitor the efficiency of feature representation during the training period. Experimental results demonstrate that the proposed method has competitive advantages over involved contrast methods.

A cartridge-based turning specimen holder with wireless tilt angle measurement for magnetic induction mapping in the transmission electron microscope

Magnetic induction mapping in the transmission electron microscope using phase contrast techniques such as off-axis electron holography and differential phase contrast imaging often requires the separation of the magnetic contribution to the recorded signal from the electrostatic contribution. When using off-axis electron holography, one of the experimental approaches that can be used to achieve this separation is to evaluate half of the difference between phase shift images that have been recorded before and after turning the sample over. Here, we introduce a cartridge-based sample mounting system, which is based on an existing on-axis tomography specimen holder and can be used to turn a sample over inside the electron microscope, thereby avoiding the need to remove the holder from the microscope to turn the sample over manually. We present three cartridge designs, which are compatible with all pole piece designs and can be used to support conventional 3-mm-diameter sample grids, Si3N4-based membrane chips and needle-shaped specimens. We make use of a wireless inclinometer that has a precision of 0.1° to monitor the sample holder tilt angle independently of the microscope goniometer readout. We also highlight the need to remove geometrical image distortions when aligning pairs of phase shift images that have been recorded before and after turning the sample over. The capabilities of the cartridge-based specimen holder and the turning approach are demonstrated by using off-axis electron holography to record magnetic induction maps of lithographically-patterned soft magnetic Co elements, a focused ion beam milled hard magnetic Nd-Fe-B lamella and an array of four Fe3O4 nanocrystals.

Fast geometric distortion correction using a deep neural network: Implementation for the 1 Tesla MRI-Linac system.

Combining high-resolution magnetic resonance imaging (MRI) with a linear accelerator (Linac) as a single MRI-Linac system provides the capability to monitor intra-fractional motion and anatomical changes during radiotherapy, which facilitates more accurate delivery of radiation dose to the tumor and less exposure to healthy tissue. The gradient nonlinearity (GNL)-induced distortions in MRI, however, hinder the implementation of MRI-Linac system in image-guided radiotherapy where highly accurate geometry and anatomy of the target tumor is indispensable. To correct the geometric distortions in MR images, in particular, for the 1 Tesla (T) MRI-Linac system, a deep fully connected neural network was proposed to automatically learn the intricate relationship between the undistorted (theoretical) and distorted (real) space. A dataset, consisting of spatial samples acquired by phantom measurement that covers both inside and outside the working diameter of spherical volume (DSV), was utilized for training the neural network, which offers the ability to describe subtle deviations of the GNL field within the entire region of interest (ROI). The performance of the proposed method was evaluated on MR images of a three-dimensional (3D) phantom and the pelvic region of an adult volunteer scanned in the 1T MRI-Linac system. The experimental results showed that the severe geometric distortions within the entire ROI had been successfully corrected with an error less than the pixel size. Also, the presented network is highly efficient, which achieved significant improvement in terms of computational efficiency compared to existing methods. The feasibility of the presented deep neural network for characterizing the GNL field deviations in the 1T MRI-Linac system was demonstrated in this study, which shows promise in facilitating the MRI-Linac system to be routinely implemented in real-time MRI-guided radiotherapy.

Detecting Matching Blunders of Multi-Source Remote Sensing Images via Graph Theory.

Large radiometric and geometric distortion in multi-source images leads to fewer matching points with high matching blunder ratios, and global geometric relationship models between multi-sensor images are inexplicit. Thus, traditional matching blunder detection methods cannot work effectively. To address this problem, we propose two matching blunder detection methods based on graph theory. The proposed methods can build statistically significant clusters in the case of few matching points with high matching blunder ratios, and use local geometric similarity constraints to detect matching blunders when the global geometric relationship is not explicit. The first method (named the complete graph-based method) uses clusters constructed by matched triangles in complete graphs to encode the local geometric similarity of images, and it can detect matching blunders effectively without considering the global geometric relationship. The second method uses the triangular irregular network (TIN) graph to approximate a complete graph to reduce to computational complexity of the first method. We name this the TIN graph-based method. Experiments show that the two graph-based methods outperform the classical random sample consensus (RANSAC)-based method in recognition rate, false rate, number of remaining matching point pairs, dispersion, positional accuracy in simulated and real data (image pairs from Gaofen1, near infrared ray of Gaofen1, Gaofen2, panchromatic Landsat, Ziyuan3, Jilin1and unmanned aerial vehicle). Notably, in most cases, the mean false rates of RANSAC, the complete graph-based method and the TIN graph-based method in simulated data experiments are 0.50, 0.26 and 0.14, respectively. In addition, the mean positional accuracy (RMSE measured in units of pixels) of the three methods is 2.6, 1.4 and 1.5 in real data experiments, respectively. Furthermore, when matching blunder ratio is no higher than 50%, the computation time of the TIN graph-based method is nearly equal to that of the RANSAC-based method, and roughly 2 to 40 times less than that of the complete graph-based method.

Aerial mapping based on arrangement of optical electron cameras

Subject of Research. The paper proposes an approach to aerial mapping that provides the photogrammetric quality of images necessary for creating orthophotoplans with high cartographic similarity. The topicality of the approach is determined by cartographic similarity reduction of the area orthophotoplans in case of automated processing of images obtained from an unmanned aerial vehicle in disturbed flight conditions. In particular, artifacts are formed on orthophotoplans that reduce the area representation adequacy in the image and prevent the correct visual interpretation of images. We propose an approach that provides planned area images, and after their automated processing orthophotoplans of places are formed with improved cartographic similarity. Method. The aerial mapping approach is based on the idea of applying the arrangement of optical-electronic cameras that analyze navigation measurement data. The proposed approach gives the possibility to minimize image perspective geometric distortions on pitch, roll and yaw that occur when an unmanned aircraft turns around during flight. Consequently, the conditions for planned aerial photography are met and, as a result, aerial images with the required photogrammetric quality are obtained. The absence of perspective geometric distortions in the images provides the creation of the area orthophotoplan without visible distortions. Main Results. A model of an aerial image geometric distortions has been developed that analyzes the effect of the optical- electronic camera sight line deviation from the direction to nadir on the occurrence of perspective geometric image distortions. Calculation results are presented for parameters of the frame projection on the earth surface for lenses with different angular fields of view. Following on from the results, an approach to aerial mapping is proposed using an optical-electronic camera arrangement that provides planned area images in the conditions of an unmanned aerial vehicle maneuvering. Practical Relevance. The arrangement of optoelectronic cameras in aerial mapping makes it possible to get planned images without additional technical means of shooting equipment stabilization and ensures the aerodynamic quality of an unmanned aerial vehicle airframe. In addition, the application of the proposed technical solution maintains the transfer characteristics of lenses of optoelectronic cameras installed in the body of an unmanned aerial vehicle and functioning in conditions of significant changes in the ambient temperature. The results of experiments demonstrate an increase in the cartographic similarity of orthophotoplans when selecting images obtained by applying the arrangement of optoelectronic cameras for aerial photography.

Performance of TGSE BLADE DWI compared with RESOLVE DWI in the diagnosis of cholesteatoma

BackgroundBased on its high resolution in soft tissue, MRI, especially diffusion-weighted imaging (DWI), is increasingly important in the evaluation of cholesteatoma. The purpose of this study was to evaluate the role of the 2D turbo gradient- and spin-echo (TGSE) diffusion-weighted (DW) pulse sequence with the BLADE trajectory technique in the diagnosis of cholesteatoma at 3 T and to qualitatively and quantitatively compare image quality between the TGSE BLADE and RESOLVE methods.MethodA total of 42 patients (23 males, 19 females; age range, 7–65 years; mean, 40.1 years) with surgically confirmed cholesteatoma in the middle ear were enrolled in this study. All patients underwent DWI (both a prototype TGSE BLADE DWI sequence and the RESOLVE DWI sequence) using a 3-T scanner with a 64-channel brain coil.Qualitative imaging parameters (imaging sharpness, geometric distortion, ghosting artifacts, and overall imaging quality) and quantitative imaging parameters (apparent diffusion coefficient [ADC], signal-to-noise ratio [SNR], contrast, and contrast-to-noise ratio [CNR]) were assessed for the two diffusion acquisition techniques by two independent radiologists.ResultA comparison of qualitative scores indicated that TGSE BLADE DWI produced less geometric distortion, fewer ghosting artifacts (P < 0.001) and higher image quality (P < 0.001) than were observed for RESOLVE DWI. A comparison of the evaluated quantitative image parameters between TGSE and RESOLVE showed that TGSE BLADE DWI produced a significantly lower SNR (P < 0.001) and higher parameter values (both contrast and CNR (P < 0.001)) than were found for RESOLVE DWI.The ADC (P < 0.001) was significantly lower for TGSE BLADE DWI (0.763 × 10− 3 mm2/s) than RESOLVE DWI (0.928 × 10− 3 mm2/s).ConclusionCompared with RESOLVE DWI, TGSE BLADE DWI significantly improved the image quality of cholesteatoma by reducing magnetic sensitive artifacts, distortion, and blurring. TGSE BLADE DWI is more valuable than RESOLVE DWI for the diagnosis of small-sized (2 mm) cholesteatoma lesions. However, TGSE BLADE DWI also has some disadvantages: the whole image intensity is slightly low, so that the anatomical details of the air-bone interface are not shown well, and this shortcoming should be improved in the future.

Geometric inaccuracy and co-registration errors for CT, DynaCT and MRI images used in robotic stereotactic radiosurgery treatment planning

PurposeTo measure the combined errors due to geometric inaccuracy and image co-registration on secondary images (dynamic CT angiography (dCTA), 3D DynaCT angiography (DynaCTA), and magnetic resonance images (MRI)) that are routinely used to aid in target delineation and planning for stereotactic radiosurgery (SRS). MethodsThree phantoms (one commercial and two in-house built) and two different analysis approaches (commercial and MATLAB based) were used to quantify the magnitude of geometric image distortion and co-registration errors for different imaging modalities within CyberKnife’s MultiPlan treatment planning software. For each phantom, the combined errors were reported as a mean target registration error (TRE). The mean TRE’s for different intramodality imaging parameters (e.g., mAs, kVp, and phantom set-ups) and for dCTA, DynaCTA, and MRI systems were measured. ResultsOnly X-ray based imaging can be performed with the commercial phantom, and the mean TRE ± standard deviation values were large compared to the in-house analysis using MATLAB. With the 3D printed phantom, even drastic changes in treatment planning CT imaging protocols did not greatly influence the mean TRE (<0.5 mm for a 1 mm slice thickness CT). For all imaging modalities, the largest mean TRE was found on DynaCT, followed by T2-weighted MR images (albeit all <1 mm). ConclusionsThe user may overestimate the mean TRE if the commercial phantom and MultiPlan were used solely. The 3D printed phantom design is a sensitive and suitable quality assurance tool for measuring 3D geometric inaccuracy and co-registration errors across all imaging modalities.

弹载大视场红外线扫图像几何畸变仿真研究

弹载大视场红外线扫图像几何畸变仿真研究

Real-time extraction of water surface boundary using shipborne radar

ABSTRACTReal-time water boundary extraction with high accuracy is still a challenging problem in remote-sensing field. This article presents a shipborne water surface boundary extraction technique by integrating civilian marine radar and GPS compass. Meanwhile, a framework is developed to automatically extract water boundary from radar image. In this framework, direct transformation is adopted to rectify the geometric distortion of the radar image, morphological operation is used to fill holes and filter speckles in image, an edge tracing algorithm is design to extract image boundaries, visibility analysis and optimizations are conducted to recognize the real water surface boundary and to produce a vector map. A case study in Nanjing reach of Yangtze River are intended to validate performances of the method, and the final output of this method is verified using synchronous and detailed GPS-RTK (real-time kinematics) survey points. The experimental results demonstrate that the proposed water boundary extraction method can reach a positioning accuracy within ±1 m, which is significantly better than that of satellite-based optical remote-sensing and synthetic aperture radar (SAR) techniques, and the algorithm is computationally efficient and has the capability of real-time, full-automatic water boundary generation for various applications.

OIDC-Net: Omnidirectional Image Distortion Correction via Coarse-to-Fine Region Attention

Omnidirectional cameras have recently received significant attention in panoramic imaging systems such as virtual reality (VR) technology; however, the strong geometric distortion in omnidirectional images severely affects the object recognition and semantic understanding. In this paper, we propose an automatic omnidirectional image distortion correction approach powered by a unified learning model (OIDC-Net). This approach is applicable for almost all types of omnidirectional cameras, requiring nothing more than a distorted image. A crucial and challenging ingredient for reconstructing the real physical scene is to estimate the heterogeneous distortion coefficients in an appropriate camera model. To address this issue, we present a novel coarse-to-fine region attention mechanism to alleviate the difficulty of predicting all coefficients simultaneously. With the proposed cascade structure and deep fusion strategy, the ambiguous relationship among these heterogeneous distortion coefficients has been incrementally perceived. Our experimental results show significant improvement over the state-of-the-art methods in terms of visual appearance, while maintaining a promising quantitative performance.

Laterally Extended Field of View Imaging without Geometric Distortion using Image Stitching in Open-Configuration MRI

Open-configuration MRI for easy patient access causes a restricted imaging field of view and geometric distortion resulting in reduced reliability of the quantitation of tissue segmentation. The method proposed in this study is use of MR image stitching, which is merging divided isocentric images without geometric distortion of the same object through the table moving laterally. This study was performed using an open 0.32 T MRI system. MR imaging with lateral shift of the scanner table was conducted using an AAPM MRI Phantom. The composite image produced through the sequential generation of the same object at different table positions has been generated using the image stitching technique. Image stitching consisted of tile configurations using optimized global registration and then seamlessly blending the aligned tiles. The overall image stitching procedure reduced the geometric distortion of image at off-center regions, and the FOV in the stitched image was extended 40% laterally relative to conventional isocenter image. The maximum distortion value was about 16.8 mm in the conventional image and was reduced to &lt; 1.7 mm after the seamless image stitching procedure. Laterally extended FOV without geometric distortion was successfully acquired using seamless image stitching procedure. These methods are beneficial towards defining tissue segmentation in obese patient with large field of view in open MRI.

Blind Quality Metric of DIBR-Synthesized Images in the Discrete Wavelet Transform Domain

Free viewpoint video (FVV) has received considerable attention owing to its widespread applications in several areas such as immersive entertainment, remote surveillance and distanced education. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a real-time and reliable blind quality assessment metric is urgently required. However, the existing image quality assessment metrics are insensitive to the geometric distortions engendered by DIBR. In this research, a novel blind method of DIBR-synthesized images is proposed based on measuring geometric distortion, global sharpness and image complexity. First, a DIBR-synthesized image is decomposed into wavelet subbands by using discrete wavelet transform. Then, the Canny operator is employed to detect the edges of the binarized low-frequency subband and high-frequency subbands. The edge similarities between the binarized low-frequency subband and high-frequency subbands are further computed to quantify geometric distortions in DIBR-synthesized images. Second, the log-energies of wavelet subbands are calculated to evaluate global sharpness in DIBR-synthesized images. Third, a hybrid filter combining the autoregressive and bilateral filters is adopted to compute image complexity. Finally, the overall quality score is derived to normalize geometric distortion and global sharpness by the image complexity. Experiments show that our proposed quality method is superior to the competing reference-free state-of-the-art DIBR-synthesized image quality models.

Measurement of isocenter alignment accuracy and image distortion of an 0.35 T MR-Linac system

For hybrid devices combining magnetic resonance (MR) imaging and a linac for radiation treatment, the isocenter accuracy as well as image distortions have to be checked. This study presents a new phantom to investigate MR-Linacs in a single measurement in terms of (i) isocentricity of the irradiation and (ii) alignment of the irradiation and imaging isocenter relative to each other using polymer dosimetry gel as well as (iii) 3-dimensional (3D) geometric MR image distortions. The evaluation of the irradiated gel was performed immediately after irradiation with the imaging component of the 0.35 T MR-Linac using a T2-weighted turbo spin-echo sequence. Eight plastic grid sheets within the phantom allow for measurement of geometric distortions in 3D by comparing the positions of the grid intersections (control points) within the MR-image with their nominal position obtained from a CT-scan. The distance of irradiation and imaging isocenter in 3D was found to be (0.8 ± 0.9) mm for measurements with 32 image acquisitions. The mean distortion over the whole phantom was (0.60 ± 0.28) mm and 99.8% of the evaluated control points had distortions below 1.5 mm. These geometrical uncertainties have to be considered by additional safety margins.

Video-based tunnel luminance detection

Abstract A new luminance detection method using tunnel video monitoring systems is proposed. The method can efficiently obtain the continuous surface luminance parameters of the large detection area in tunnels. Firstly, the stability and uniformity of the cameras in a tunnel video monitoring system are calibrated. Then, a new detection method can be mainly divided into the following parts: video image stability and uniformity detection, image geometric distortion correction detection, background initialization, luminance function fitting, pixels and blocks luminance extraction, luminance uniformity detection and so on. Finally, the surface luminance and total luminance parameters can be calculated in tunnels. The experimental results show that the method achieves a high accuracy in two different conditions.

High-Accuracy Correction of a Microlens Array for Plenoptic Imaging Sensors.

Microlens array (MLA) errors in plenoptic cameras can cause the confusion or mismatching of 4D spatio-angular information in the image space, significantly affecting the accuracy and efficiency of target reconstruction. In this paper, we present a high-accuracy correction method for light fields distorted by MLA errors. Subpixel feature points are extracted from the microlens subimages of a raw image to obtain correction matrices and perform registration of the corresponding subimages at a subpixel level. The proposed method is applied for correcting MLA errors of two different categories in light-field images, namely form errors and orientation errors. Experimental results show that the proposed method can rectify the geometric and intensity distortions of raw images accurately and improve the quality of light-field refocusing. Qualitative and quantitative comparisons between images before and after correction verify the performance of our method in terms of accuracy, stability, and adaptability.

Motion Compensation for Radar Terrain Imaging Based on INS/GPS System

In order to obtain good quality radar terrain images using an aerial-based synthetic aperture radar, a motion compensation procedure must be applied. This procedure can use a precise navigation system in order to determine the aircraft’s position and velocity. A major challenge is to design a motion compensation procedure that can operate in real time, which is crucial to ensure convenient data for a human analyst. The article discusses a possibility of Inertial Measurement System (INS)/Global Positioning System (GPS) navigation system usage in such a radar imaging system. A Kalman filter algorithm designed for this system is described herein, and its modifications introduced by the authors allow the use of navigational data not aligned in time and captured with different frequencies. The presented navigation system was tested using measured data. Radar images obtained with the INS/GPS-based motion compensation system were compared to the INS-only results and images obtained without navigation corrections. The evaluation results presented in the paper show that the INS/GPS system allows for better reduction of geometric distortions in images compared to the INS-based approach, which makes it more suitable for typical applications.

Image Artifact Management for Clinical Magnetic Resonance Imaging on a 7 T Scanner Using Single-Channel Radiofrequency Transmit Mode.

The aim of this work was to devise mitigation strategies for addressing a range of image artifacts on a clinical 7 T magnetic resonance imaging scanner using the regulatory-approved single-channel radiofrequency transmit mode and vendor-supplied radiofrequency coils to facilitate clinical scanning within reasonable scan times. Optimized imaging sequence protocols were developed for routine musculoskeletal knee and neurological imaging. Sources of severe image nonuniformities were identified, and mitigation strategies were devised. A range of custom-made high permittivity dielectric pads were used to compensate for B1 and B1 inhomogeneities, and also for magnetic susceptibility-induced signal dropouts particularly in the basal regions of the temporal lobes and in the cerebellum. Significant improvements in image uniformity were obtained using dielectric pads in the knee and brain. A combination of small voxels, reduced field of view B0 shimming, and high in-plane parallel imaging factors helped to minimize signal loss in areas of high susceptibility-induced field distortions. The high inherent signal-to-noise ratio at 7 T allowed for high receiver bandwidths and thin slices to minimize chemical shift artifacts. Intermittent artifacts due to radiofrequency inversion pulse limitations (power, bandwidth) were minimized with dielectric pads. A patient with 2 implanted metallic cranial fixation devices located within the radiofrequency transmit field was successfully imaged, with minimal image geometric distortions. Challenges relating to severe image artifacts at 7 T using single-channel radiofrequency transmit functionality in the knee and brain were overcome using the approaches described in this article. The resultant high diagnostic image quality paves the way for incorporation of this technology into the routine clinical workflow. Further developmental efforts are required to expand the range of applications to other anatomical areas, and to expand the evidence- and knowledge-base relating to the safety of scanning patients with implanted metallic devices.

Aircraft altitude estimation method based on multi‐beam pitching sum and difference channels for SAR

Synthetic aperture radar (SAR) can provide high-resolution two-dimensional radar images of the target area. The error of the altitude between aircraft and the target area causes geometrical distortion of the SAR ground image, which is unfavourable for scene matching and target recognition. Existing methods, such as radar altimeters, work in the case of vertical beam irradiation. However, the highly accurate aircraft altitude estimation for SAR (under oblique irradiation) is still a challenge. In this paper, an aircraft altitude estimation method based on multi-beam pitching sum and difference channels radar echoes is proposed. The pitching sum and difference channels angle measurement principle is used to achieve accurate beam centre distance estimation, and the cyclic multiple beams are used to realise the estimation of the grazing angle deviation. Therefore, this method can realise the accuracy estimation of the aircraft altitude under oblique beam irradiation conditions. Then, the effects of various error sources on the accuracy of altitude estimation are analysed. The results of simulation and real data verify the correctness of the analysis and the validity of the proposed method.

Geometric distortions in FMCW SAR images due to inaccurate knowledge of electronic radar parameters: analysis and correction by means of corner reflectors

In the last years the Frequency Modulated Continuous Wave (FMCW) technology has been playing an ever greater role in the realization of compact, light and cheap Synthetic Aperture Radar (SAR) systems to be mounted onboard small, low altitude platforms such as airplanes, helicopters and drones.To correctly focus FMCW SAR images, it is necessary to accurately know some system parameters, including the frequency sweep rate of the signal transmitted by the radar. It may happen, however, that this frequency sweep rate is not very accurately measured by the radar provider, and thus an incorrect value of this parameter is used during the SAR data focusing procedure. This may produce serious geometric distortion effects in the focused FMCW SAR images. To circumvent these problems, in this work we present a procedure that estimates the frequency sweep rate actually employed by the FMCW radar, thus providing a key information that can be then profitably used to achieve the correct focusing of the SAR data acquired by the radar system at hand. More specifically, we propose an algorithm that exploits on one side the focused SAR images corrupted by the geometric distortion effects induced by the inaccurate knowledge of this radar parameter, and on the other side the very precise in-situ measurements of the positions of a limited number of Corner Reflectors (CRs) properly deployed over the observed scene.The effectiveness of the proposed algorithm has been tested on real data acquired by an airborne X-band FMCW SAR system.

Evaluation of the performance of radiological monitors in use, cities Salvador (BA) and Florianópolis (SC)

Evaluate the performance of the monitors used for diagnosis based on the parameters defined by AAMP. Materials and Methods: Using calibrated instrumentation traceable to NIST and RBC, were evaluated in 15 monitors, according to the procedures described in AAMP's report 03 and the Spanish protocol in the following parameters: the general aspects of image quality, geometric distortion, screen reflection and room illumination, luminance response, luminance dependence, spatial and low contrast resolution, noise, internal reflection blanking and screen chromaticity. Results: 100% compliance for geometric distortion tests and 0% compliance for the luminance dependence test. Conclusions: There are nonspecific monitors for diagnosis being used for these purposes, without routinely checking tests, in rooms with high illumination and dirt on the screens and the non-implementation or inadequacy of acceptance and quality control tests. The monitors declared by the manufacturers as diagnostic specific on average showed a higher compliance rate