Region Of Interest Position Research Articles

Quantitative Comparison of Color-Coded Parametric Imaging Technologies Based on Digital Subtraction and Digital Variance Angiography: A Retrospective Observational Study.

The evaluation of hemodynamic conditions in critical limb-threatening ischemia (CLTI) patients is inevitable in endovascular interventions. In this study, the performance of color-coded digital subtraction angiography (ccDSA) and the recently developed color-coded digital variance angiography (ccDVA) was compared in the assessment of key time parameters in lower extremity interventions. The observational study included 19 CLTI patients who underwent peripheral vascular intervention at our institution in 2020. Pre- and post-dilatational images were retrospectively processed and analyzed by a commercially available ccDSA software (Kinepict Medical Imaging Tool 6.0.3; Kinepict Health Ltd., Budapest, Hungary) and by the recently developed ccDVA technology. Two protocols were applied using both a 4 and 7.5 frames per second acquisition rate. Time-to-peak (TTP) parameters were determined in four pre- and poststenotic regions of interest (ROI), and ccDVA values were compared to ccDSA read-outs. The ccDVA technology provided practically the same TTP values as ccDSA (r = 0.99, R2 = 0.98, p < 0.0001). The correlation was extremely high independently of the applied protocol or the position of ROI; the r value was 0.99 (R2 = 0.98, p < 0.0001) in all groups. A similar correlation was observed in the change in passage time (r = 0.98, R2 = 0.96, p < 0.0001). The color-coded DVA technology can reproduce the same hemodynamic data as a commercially available DSA-based software; therefore, it has the potential to be an alternative decision-supporting tool in catheter labs.

Application of bolus tracking: The effect of ROI positions on the images quality of cervicocerebral CT angiography

BackgroundCervicocerebral CT angiography (CTA) using the bolus tracking technique has been widely used for the assessment of cerebrovascular diseases. Regions of interest (ROI) can be placed in the descending aorta, ascending aorta, and the aortic arch. However, no study has compared the arteries and veins display when when the region of interest (ROI) is placed at different sites. In this study, we showed the impact of ROI positions on the image quality of cervicocerebral CTA. MethodsTwo hundred and seventy patients who underwent cervicocerebral CTA with bolus tracking technique were randomly divided into three groups based on the position of the ROI placement: ascending aorta (Group 1, n = 90), aortic arch (Group 2, n = 90), and descending aorta (Group 3, n = 90). The scanning parameters and contrast agent injection protocols were consistent across all groups. Three observers independently assessed the objective image quality, while two observers jointly assessed the subjective image quality using a grade scale: poor (grade 1), average (grade 2), good (grade 3), and excellent (grade 4). The differences in intravascular CT values, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), AVCR (arterial venous contrast ratio), and subjective image quality scores were compared among the three groups. ResultsThe CT values of the intracranial veins (superior sagittal sinus, ethmoid sinus and great cerebral vein) in group 1 were significantly lower than those in group 3 (p < 0.001). However, no significant differences were observed in CT values, SNR and CNR in the internal carotid artery and middle cerebral artery among the three groups. The proportion of images with grade 4 was significantly higher in group 1 than group 2 and 3 (41.1% vs 15.6% and 13.3%, p < 0.001). The proportion of images with grade 1 was significantly lower in group 1 than group 2 and 3 (1.1% vs 6.6% and 17.8%, p < 0.001). ConclusionThe ROI positions for cervicocerebral CTA did not affect the arterial image quality, but venous structures imaging was affected when the ROI was placed in the ascending aorta.

Abstract 3771: 3D correlated multi-scale cellular and molecular architecture of solid tumors

Abstract A solid tumor presents heterogeneous 3D structures at tissue, cell, and molecule levels. To develop advanced cancer diagnostics and therapies, it is important to understand in-depth cellular and molecular architecture of a tumor at multiple scales. Here we introduce novel optical microscopy methodologies for in-depth 3D spatial analysis of tumor tissues: 1) LED photobleaching-mediated 3D multiplex immunofluorescence (IF) microscopy, 2) Correlated 3D multi-resolution optical microscopy, and 3) 3D tissue region-based cell type-selective multi-omics. We built a high-power LED light irradiator with a broad emission spectrum (490-700 nm) that bleaches a broad wavelength of fluorescence signals simultaneously throughout an optically cleared, 400 µm-thick tumor tissue. Cyclic workflow involving IF staining, optical tissue clearing, 3D confocal microscopy, and LED photobleaching enables visualization of multiple cell types in the same whole 400 µm-thick tumor tissue after computational 3D image registration. The constructed multiplex image offers comprehensive 3D cellular landscape of a tumor. We also developed a method for tracking regions of interest (ROIs) in the middle of a large tumor tissue using a UV-activated visible dye in light sheet microscopy. Light sheet microscopy allows imaging an optically cleared large-sized tumor tissue at a low spatial, tissue resolution. To mark the ROI positions on a tumor, the dye is infused into agarose gel surrounding the tumor tissue and be activated and present purple-colored lines where are exposed to UV light sheets in light sheet microscopy. The tumor tissue was physically sectioned at the marked ROI positions using a vibratome after reversing tissue clearing process. Sequential IF staining and high-resolution confocal microscopy permit for visualizing detailed cellular compositions of the ROIs in the tumor. The tissue and cellular-resolution 3D images from light sheet and confocal microscopy are correlatively integrated to display ‘Google Earth’-like multi-scale view of a tumor tissue. To further analyze the ROIs of a tumor at molecular level, we have developed optical microscope-mediated fluorescence lithography methods that allow fluorescently labeling of a selected cell type in ROIs of an optically cleared 3D tumor tissue. After wash free from clearing solution and dissociation of the tumor into cells, fluorescence-marked, intact cells from the ROIs are collected through flow cell sorting. Proteins and mRNAs are extracted from the collected cells and sent to LC-MS/MS analysis and RNA sequencing. The spatial multi-omics method provides in-depth molecular information of selected cells in the ROIs of a tumor. We believe all these 3D microscopy methods will provide powerful spatial analysis tools for better understanding cellular and molecular architecture of solid tumors. Citation Format: Steve Seung-Young Lee, Yi-Chien Wu, Jingtian Zheng, Elie Abi Khalil, Samuel Wang, Alexander Lippert, Joshua Plank. 3D correlated multi-scale cellular and molecular architecture of solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3771.

Identification of cladding layer offset using infrared temperature measurement and deep learning for WAAM

In the wire arc additive manufacturing (WAAM) procedure, the stability of the cladding layer’s formation directly impacts the final dimensional precision of the WAAM weldment. To achieve high-precision forming of the WAAM weldment, online monitoring of the cladding layer offset is essential. This article explores the monitoring technology for the cladding layer offset in the WAAM process and introduces a cladding layer offset monitoring technique using infrared temperature measurement and deep learning. First, a temperature field measurement system for the WAAM weldment is set up using an infrared thermal imager. Next, a region of interest (ROI) is selected on the weldment sidewall. The optimised histogram of oriented gradient (HOG) algorithm is then employed to extract the temperature distribution characteristics of the ROI. The separability of the temperature field on the weldment sidewall is analysed under various offset degrees of the cladding layer. Finally, using the temperature image of the ROI as input, a cladding layer offset recognition model is developed using a convolutional neural network (CNN). This study also evaluates the effect of the selected ROI position on the recognition precision of the model for the cladding layer offset. Experimental results indicate that the recognition accuracy of the model for cladding layer offset, as presented in this article, exceeds 99%. Moreover, the model demonstrates strong robustness, further enriching the intelligent monitoring methods for the WAAM process.

A Study on the Optimization of Contrast Enhancement in Cerebrovascular CT in Hemorrhagic Stroke Patients

During the brain computed tomography angiography (Brain CTA) test of hemorrhagic stroke patients, we tried to find out the test method for optimizing contrast enhancement of cerebrovascular vessels by changing the location of the region of interest (ROI) and scan delay time. From September 2022 to February 2023, 80 patients who visited the emergency room and performed a Brain CTA test were tested, and 10 people in control group without disease were ROI set at C3 to C4 level and performed a test by 6-second delay scan as soon as contrast enhancement was performed on common carotid artery (CCA) with the naked eye. 40 people in the hemorrhagic stroke experiment group A setting the same test method as the control group were tested after A-0; 6 second, A-1; 8 second, A-2; 10 second, A-3; 12-second delay for 10 people each, and 30 people in experiment group B setting ROI at circle of willis level and as soon as contrast enhancement was performed in the middle cerebral artery (MCA) were tested after B-1; 2 second, B-2; 4 second, B-3; 6-second delay for 10 people each. The evaluation methods include quantitative evaluation that compares and analyzes the mean HU values and percentage values of internal carotid artery (ICA), MCA, superior sagittal sinus (SSS), and internal jugular vein (IJV) of the control group and experimental groups A and B, qualitative evaluation through reconstructed images, and significance evaluation was conducted using an independent sample t-test. As a result of the quantitative evaluation, the mean HU value of MCA in the experimental group was measured lower than that of the control group, 369 HU, but was generally close to 300 HU. In the MCA vs SSS percentage value, the experimental group B-2 was 0.7%, the closest value to the control group. As a result of the blind test through reconstructed images as a qualitative evaluation, the control group scored the highest with 16 points, and in the experimental group B-2 scored the highest with 15 points. As a result of significance evaluation through an independent sample t-test, the p-value of the control group and the experimental group B-2 was 0.408, which was evaluated as having no significant difference, and other experimental groups were evaluated that there was a significant difference. As a result of analyzing the test performed by changing the ROI position and scan delay time of control and experimental groups A and B, setting the ROI at the circle of willis level and testing after 4-second delay as soon as contrast enhancement is made in MCA will be useful for Brain CTA test in hemorrhagic stroke patients.

Dose-consistent dynamic SPECT

BackgroundCoronary flow reserve (CFR) values measured by dynamic SPECT systems are typically consistent with other modalities (e.g., PET). However, large discrepancies are often observed for individual patients. Positioning of the region-of-interest (ROI), representing the arterial input function (AIF) could explain some of these discrepancies. We explored the possibility of positioning the ROI in a manner that evaluates its consistency with patient-based injected radiotracer doses. MethodsDose-consistent dynamic SPECT methodology was introduced, and its application was demonstrated in a twenty-patient clinical study. The effect of various ROI positions was investigated and comparison to myocardial perfusion imaging was performed. ResultsMean AIF ratios were consistent with the injected dose ratios for all examined ROI positions. Good agreement (> 80%) between total perfusion deficit and CFR was found in the detection of obstructive CAD patients for all ROIs considered. However, for individual patients, significant dependence on ROI position was observed (altering CFR by typically 30%). The proposed methodology’s uncertainty was evaluated (~ 7%) and found to be smaller than the variability due to choice of ROI position. ConclusionDose-consistent dynamic SPECT may contribute to evaluating uncertainty of CFR measurements and may potentially decrease uncertainty by allowing improved ROI positioning for individual patients.

Factors influencing the Shear Wave Elastography evaluation of the patellar tendon.

There is no clear standardization for tendon Shear Wave Elastography (SWE), and data regarding the factors that influence the correctness of evaluation are scarce. We aimed to determine the intra- and interobserver agreement in patellar tendon SWE, and to establish the influence of various factors on elasticity values. We recruited 37 healthy volunteers; SWE of the patellar tendon was performed by two examiners. The following factors were analyzed: probe frequency, degree of joint flexion, size of region of interest (ROI), distance of the color box from the probe footprint, utilization of coupling gel as standoff, and the effect of physical exercise on elastic modulus values. Highest overall interobserver [k=0.767, 95%CI (0.717-0.799), p<0.001] and intraobserver agreement [k=0.920 (0.909-0.929) for examiner 1, k=0.891 (0.875-0.905) for examiner 2] was obtained with the knee in the neutral position, using the L18-5 probe. With the knee flexed at 30º and 45º, the elasticity values were higher compared to the neutral position (p<0.001). With the probe immersed in 0.25 and 0.50 cm coupling gel, the median values were lower compared to the probe placed on the skin (p=0.001, p=0.018). The ROI dimensions and the placement of the SWE box at the level of the skin or at 0.5 cm below skin did not significantly influence the elastic modulus. After physical exercise, the elasticity values decreased in the proximal and middle portion of the tendon (p=0.002, p<0.001). The best results obtained in patellar tendon SWE were with the knee in neutral position, in the proximal or middle tendon, after 10 minutes of relaxation and with the probe placed directly on the skin with minimal pressure. The size and position of ROI do not significantly influence the examination.

Variation of cerebrospinal fluid in specific regions regulates focality in transcranial direct current stimulation.

BackgroundConventionally, transcranial direct current stimulation (tDCS) aims to focalize the current reaching the target region-of-interest (ROI). The focality can be quantified by the dose-target-determination-index (DTDI). Despite having a uniform tDCS setup, some individuals receive focal stimulation (high DTDI) while others show reduced focality (“non-focal”). The volume of cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) underlying each ROI govern the tDCS current distribution inside the brain, thereby regulating focality.AimTo determine the regional volume parameters that differentiate the focal and non-focal groups.MethodsT1-weighted images of the brain from 300 age-sex matched adults were divided into three equal groups- (a) Young (20 ≤ × < 40 years), (b) Middle (40 ≤ × < 60 years), and (c) Older (60 ≤ × < 80 years). For each group, inter and intra-hemispheric montages with electrodes at (1) F3 and right supraorbital region (F3-RSO), and (2) CP5 and Cz (CP5-Cz) were simulated, targeting the left- Dorsolateral Prefrontal Cortex (DLPFC) and -Inferior Parietal Lobule (IPL), respectively. Both montages were simulated for two current doses (1 and 2 mA). For each individual head simulated for a tDCS configuration (montage and dose), the current density at each region-of-interest (ROI) and their DTDI were calculated. The individuals were categorized into two groups- (1) Focal (DTDI ≥ 0.75), and (2) Non-focal (DTDI < 0.75). The regional volume of CSF, GM, and WM of all the ROIs was determined. For each tDCS configuration and ROI, three 3-way analysis of variance was performed considering- (i) GM, (ii) WM, and (iii) CSF as the dependent variable (DV). The age group, sex, and focality group were the between-subject factors. For a given ROI, if any of the 3 DV’s showed a significant main effect or interaction involving the focality group, then that ROI was classified as a “focal ROI.”ResultsRegional CSF was the principal determinant of focality. For interhemispheric F3-RSO montage, interaction effect (p < 0.05) of age and focality was observed at Left Caudate Nucleus, with the focal group exhibiting higher CSF volume. The CSF volume of focal ROI correlated positively (r ∼ 0.16, p < 0.05) with the current density at the target ROI (DLPFC). For intrahemispheric CP5-Cz montage, a significant (p < 0.05) main effect was observed at the left pre- and post-central gyrus, with the focal group showing lower CSF volume. The CSF volume correlated negatively (r ∼ –0.16, p < 0.05) with current density at left IPL. The results were consistent for both current doses.ConclusionThe CSF channels the flow of tDCS current between electrodes with focal ROIs acting like reservoirs of current. The position of focal ROI in the channel determines the stimulation intensity at the target ROI. For focal stimulation in interhemispheric F3-RSO, the proximity of focal ROI reserves the current density at the target ROI (DLPFC). In contrast, for intrahemispheric montage (CP5-Cz), the far-end location of focal ROI reduces the current density at the target (IPL).

An Image Importance Partition-Based Compression Method for COVID-19 Computed Tomography Scan

As the coronavirus disease 2019 (COVID-19) spreads around the world, industrial automated medical diagnosis systems have been developed, which complete a large amount of medical diagnosis work through computed tomography (CT) images. In these systems, how to quickly store and transmit such a large amount of CT image information has important research significance. In this article, a more targeted COVID-19 chest CT image codec is proposed to make image data not only occupy less space but also have higher image quality. First, the bilateral lung contours are extracted to calculate the position information of the region of interest (ROI). Then, a CT image is classified into four types of nonuniform image blocks according to the characteristics of COVID-19 chest CT images and ROI position information. Next, a series of new transformations are proposed for more efficient transform coding. Finally, a flexible quantization strategy is proposed for the adaptive quantization part. In the experiments, the proposed method is superior to some of the existing methods with similar computational complexity. At the same bit rate, it significantly improves the image quality. This means that chest CT images can still be used for disease diagnosis while taking up less space. In addition, because of the low computational complexity of the proposed method, it can be more easily embedded into the CT equipment with low computational power.

Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable: validation in multi-centre multi-vendor data

BackgroundThe objective of the study was to investigate variability and agreement of the commonly used image processing method “n-SD from remote” and in particular for quantifying myocardial infarction by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR). LGE-CMR in tandem with the analysis method “n-SD from remote” represents the current reference standard for infarct quantification. This analytic method utilizes regions of interest (ROIs) and defines infarct as the tissue with a set number of standard deviations (SD) above the signal intensity of remote nulled myocardium. There is no consensus on what the set number of SD is supposed to be. Little is known about how size and location of ROIs and underlying signal properties in the LGE images affect results. Furthermore, the method is frequently used elsewhere in medical imaging often without careful validation. Therefore, the usage of the “n-SD” method warrants a thorough validation.MethodsData from 214 patients from two multi-center cardioprotection trials were included. Infarct size from different remote ROI positions, ROI size, and number of standard deviations (“n-SD”) were compared with reference core lab delineations.ResultsVariability in infarct size caused by varying ROI position, ROI size, and “n-SD” was 47%, 48%, and 40%, respectively. The agreement between the “n-SD from remote” method and the reference infarct size by core lab delineations was low. Optimal “n-SD” threshold computed on a slice-by-slice basis showed high variability, n = 5.3 ± 2.2.ConclusionThe “n-SD from remote” method is unreliable for infarct quantification due to high variability which depends on different placement and size of remote ROI, number “n-SD”, and image signal properties related to the CMR-scanner and sequence used. Therefore, the “n-SD from remote” method should not be used, instead methods validated against an independent standard are recommended.

Cross-Connected Bidirectional Pyramid Network for Infrared Small-Dim Target Detection

Infrared small-dim target detection is an important technology in the fields of infrared guidance, anti-missile, and tracking system. Due to the small size of targets, no obvious structure information, and low image signal-to-noise ratio (SNR), infrared small-dim target detection is still a challenging task. In this letter, a cross-connected bidirectional pyramid network (CBP-Net) is proposed for infrared small-dim target detection. The main body of the CBP-Net is to embed a bottom-up pyramid in the feature pyramid network (FPN), which is designed to provide more comprehensive target information by connecting with the original multi-scale features and the top-down pyramid. The bottom-up pyramid together with the top-down pyramid forms the proposed bidirectional pyramid structure. Then, an region of interest (ROI) feature augment module (RFA) composed of deformable ROI pooling and position attention is designed to fuse multi-scale ROI features and enhance the spatial information of the small-dim target. Besides, a regular constraint loss (RCL) is introduced to restrict multi-scale feature fusion to learn more precise target location information. Experimental results on two challenging datasets show that the performance of the proposed CBP-Net is superior to the state-of-the-art methods.

Sources of Variability in Shear Wave Speed and Dispersion Quantification with Ultrasound Elastography: A Phantom Study.

There is a growing interest in quantifying shear-wave dispersion (SWD) with ultrasound shear-wave elastography (SWE). Recent studies suggest that SWD complements shear-wave speed (SWS) in diffuse liver disease diagnosis. To accurately interpret these metrics in clinical practice, we analyzed the impact of operator-dependent acquisition parameters on SWD and SWS measurements. Considered parameters were the acquisition depth, lateral position and size of the region of interest (ROI), as well as the size of the SWE acquisition box. Measurements were performed using the Canon Aplio i800 system (Canon Medical Systems, Otawara, Tochigi, Japan) and four homogeneous elasticity phantoms with certified stiffness values ranging from 3.7 to 44 kPa. In general, SWD exhibited two to three times greater variability than SWS. The acquisition depth was the main variance-contributing factor for both SWS and SWD, which decayed significantly with depth. The lateral ROI position contributed as much as the acquisition depth to the total variance in SWD. Locations close to the initial shear-wave excitation pulse were more robust to biases because of inaccurate probe-phantom coupling. The size of the ROI and acquisition box did not introduce significant variations. These results suggest that future guidelines on multiparametric elastography should account for the depth- and lateral-dependent variability of measurements.

Planar-Equirectangular Image Stitching

The 360 cameras have served as a convenient tool for people to record their special moments or everyday lives. The supported panoramic view allowed for an immersive experience with a virtual reality (VR) headset, thus adding viewer enjoyment. Nevertheless, they cannot deliver the best angular resolution images that a perspective camera may support. We put forward a solution by placing the perspective camera planar image onto the pertinent 360 camera equirectangular image region of interest (ROI) through planar-equirectangular image stitching. The proposed method includes (1) tangent image-based stitching pipeline to solve the equirectangular image spherical distortion, (2) feature matching scheme to increase correct feature match count, (3) ROI detection to find the relevant ROI on the equirectangular image, and (4) human visual system (HVS)-based image alignment to tackle the parallax error. The qualitative and quantitative experiments showed improvement of the proposed planar-equirectangular image stitching over existing approaches on a collected dataset: (1) less distortion on the stitching result, (2) 29.0% increased on correct matches, (3) 5.72 ROI position error from the ground truth and (4) lower aggregated alignment-distortion error over existing alignment approaches. We discuss possible improvement points and future research directions.

Examination of the confounding effect of subcutaneous fat on muscle echo intensity utilizing exogenous fat.

We aimed to provide an unbiased estimate of the confounding effect of subcutaneous fat thickness on ultrasound echo intensity (EI) measures of muscle quality. The effect of fat thickness on EI was verified for an approximate range of 0 to 3 cm of fat using exogeneous layers of pork fat over the human tibialis anterior muscle. Sonograms were obtained (i) with focus constant across fat thickness conditions, and (ii) with focus position adjusted to the muscle region of interest (ROI) position for each fat thickness level. In agreement with our hypothesis, increasing fat between the probe and the ROI resulted in a decrease in EI. This overestimating effect of fat on muscle quality differs between sonograms with constant focus and sonograms with focus position adjusted to the vertical displacement in ROI position that occurs for different levels of fat thickness. Correcting equations to account for the overestimating effect of fat on muscle quality are provided for both focus conditions. This is the first study to systematically analyze the confounding effect of fat thickness as an independent factor and the provided equations can be used for improved accuracy in estimates of muscle quality in obese/overweight subjects/patients. Novelty: The independent confounding effect of subcutaneous fat thickness on ultrasound (US) estimates of muscle quality was quantified. US estimates of muscle quality depend on whether focus is adjusted to the muscle region of interest or not. Equations for correcting muscle quality estimates are provided.

An Automated Method for Quality Control in MRI Systems: Methods and Considerations

Objective: The purpose of this study was to develop an automated method for performing quality control (QC) tests in magnetic resonance imaging (MRI) systems, investigate the effect of different definitions of QC parameters and its sensitivity with respect to variations in regions of interest (ROI) positioning, and validate the reliability of the automated method by comparison with results from manual evaluations. Materials and Methods: Magnetic Resonance imaging MRI used for acceptance and routine QC tests from five MRI systems were selected. All QC tests were performed using the American College of Radiology (ACR) MRI accreditation phantom. The only selection criterion was that in the same QC test, images from two identical sequential sequences should be available. The study was focused on four QC parameters: percent signal ghosting (PSG), percent image uniformity (PIU), signal-to-noise ratio (SNR), and SNR uniformity (SNRU), whose values are calculated using the mean signal and the standard deviation of ROIs defined within the phantom image or in the background. The variability of manual ROIs placement was emulated by the software using random variables that follow appropriate normal distributions. Results: Twenty-one paired sequences were employed. The automated test results for PIU were in good agreement with manual results. However, the PSG values were found to vary depending on the selection of ROIs with respect to the phantom. The values of SNR and SNRU also vary significantly, depending on the combination of the two out of the four standard rectangular ROIs. Furthermore, the methodology used for SNR and SNRU calculation also had significant effect on the results. Conclusions: The automated method standardizes the position of ROIs with respect to the ACR phantom image and allows for reproducible QC results.

Image-Based Gimbal Control in a Drone for Centering Photovoltaic Modules in a Thermal Image

Recently, there have been many types of research applying drones with a thermal camera to detect deteriorations in photovoltaic (PV) modules. A thermal camera can measure temperatures on the surface of PV modules and find the deteriorated area. However, a thermal camera generally has a lower resolution than a visible camera because of the limitations of cost. Due to different resolutions between the visible and thermal cameras, there are often invalid frames from a thermal camera. In this paper, we describe a gimbal controller with a real-time image processing algorithm to control the angle of the camera to position the region of interest (ROI) in the center of target PV modules to solve this problem. We derived the horizontal angle and vertical position of ROI in visible images using image processing algorithms such as the Hough transform. These values are converted into a PID control signal for controlling the gimbal. This process makes the thermal camera capture the effective area of target PV modules. Finally, experimental results showed that the photovoltaic module’s control area was properly located at the center of the thermal image.

The reliability of the computed tomography perfusion parameters as a predictor of colorectal cancer grade: influence of tumor region of interest position

BackgroundThe aim of this study is to prospectively determine whether the computed tomography perfusion (CTP) can predict the tumor grade in colorectal cancer (CRC), and investigation of the best position of the tumor region of interest (ROI) could improve the tumor grade differentiation.ResultsThe mean blood flow (mBF) at the tumor edge was significantly different among different tumor grades with the highest value noted in moderately differentiated and the lowest value in poorly differentiated CRC (111.67 ± 38.91 vs. 52.25 ± 21.97 ml/min/100 g, respectively, P = 0.03). At the tumor center, the BF and blood volume (BV) showed highest value in moderately differentiated and the lowest value in poorly differentiated CRC (P < 0.001, 0.02 respectively). The ROC curve revealed that the BF at the tumor edge showed its best results as regard its sensitivity 73.9% and specificity 82.1% in the characterization of moderately differentiated CRC from the other subtypes at > 92.2 ml/100 g/min cut off point and their AUC and P value were (0.82 and < 0.001 respectively), while the AUC of the BF at the tumor center was 0.81 and its P value was 0.03. In the characterization of poorly differentiated CRC from the other subtypes, BF cut off value at < 67.32 ml/100 g/min at the tumor edge showed the best performance of its sensitivity 88% and specificity 88% with 0.92 AUC and P value was < 0.001, while the AUC of the BF at the tumor center was 0.89. BF was higher at the edge than at the center of the tumor (88.53 ± 22.45 vs. 78.79 ± 28.98 ml/min/100 g; P < 0.001 respectively).ConclusionsPCT could help in prediction of the poorly and the moderately differentiated CRC and the mBF was the most reliable parameter in prediction of the grade. The variation in ROI position has no substantial difference in the prediction of the tumor grade; however, this variation has a significant impact on the measurements of the PCT parameters especially the BF.

A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position

Medical images contain a large amount of patients' private information. The theft and destruction of medical images will cause irreparable losses to patients and medical institutions. In order to detect the region of interest(ROI) accurately, avoid leakage of ROI position information, and realize lossless recovery of transform domain encryption, we propose a novel lossless medical image encryption scheme based on game theory with optimized ROI parameters and hidden ROI position. In the encryption process, the ROI is a pixel-level transformed to achieve the lossless decryption of medical images and protect medical image information from loss. At the same time, the position information of the ROI is effectively hidden, and leakage of the position information during transmission is avoided. In addition, the quantum cell neural network(QCNN) hyperchaotic system generates random sequence to scramble and diffuse the ROI. Most important of all, the quantitative analysis method of ROI parameters is given, and the optimal balance between encryption speed and encryption security performance is achieved by using game theory. Simulation experiments and numerical analysis verify that the scheme achieves optimized and lossless encryption and decryption of images, and can flexibly and reliably protect the medical images of different types and structures against various attacks.

Fully automated dual-resolution serial optical coherence tomography aimed at diffusion MRI validation in whole mouse brains.

.An automated dual-resolution serial optical coherence tomography (2R-SOCT) scanner is developed. The serial histology system combines a low-resolution () OCT with a high-resolution () OCT to acquire whole mouse brains at low resolution and to target specific regions of interest (ROIs) at high resolution. The ROIs positions are selected either manually by the microscope operator or using an automated ROI positioning selection algorithm. Additionally, a multimodal and multiresolution registration pipeline is developed in order to align the 2R-SOCT data onto diffusion MRI (dMRI) data acquired in the same ex vivo mouse brains prior to automated histology. Using this imaging system, 3 whole mouse brains are imaged, and 250 high-resolution three-dimensional ROIs are acquired. The capability of this system to perform multimodal imaging studies is demonstrated by labeling the ROIs using a mouse brain atlas and by categorizing the ROIs based on their associated dMRI measures. This reveals a good correspondence of the tissue microstructure imaged by the high-resolution OCT with various dMRI measures such as fractional anisotropy, number of fiber orientations, apparent fiber density, orientation dispersion, and intracellular volume fraction.

Limited Accuracy of Colour Doppler Ultrasound Dynamic Tissue Perfusion Measurement in Diabetic Adults.

Dynamic tissue perfusion measurement (DTPM) is a pre-described and available method in pediatric ultrasound to quantify tissue perfusion in renal Doppler ultrasound by particular video analysis software. This study evaluates DTPM during single and between repeated visits after 6 months, calibrates repeated DTPM within different region of interest (ROI) and compares DTPM with kidney function markers in adult patients with early diabetic nephropathy (n = 17). During repeated measurements, no association of readings at the same patients in the same (n = 3 readings) as well as repeated visit (n = 2 visits) could be retrieved. No association between DTPM, MDRD-GFR, albuminuria, age and duration of diabetes was observed. These negative results are presumably related to inconsistency of DTPM due to non-fixed ROI position as could be shown in calibrating series. Further development of the method should be performed to enable reproducible DTPM readings in adults.