Camera-based object detection is integral to advanced driver assistance systems (ADAS) and autonomous vehicle research, and RGB cameras remain indispensable for their spatial resolution and color information. This study investigates exposure time optimization for such cameras, considering image quality in dynamic ADAS scenarios. Exposure time, the period during which the camera sensor is exposed to light, directly influences the amount of information captured. In dynamic scenarios, such as those encountered in typical driving scenarios, optimizing exposure time becomes challenging due to the inherent trade-off between Signal-to-Noise Ratio (SNR) and motion blur, i.e., extending exposure time to maximize information capture increases SNR, but also increases the risk of motion blur and overexposure, particularly in low-light conditions where objects may not be fully illuminated. The study introduces a comprehensive methodology for exposure time optimization under various lighting conditions, examining its impact on image quality and computer vision performance. Traditional image quality metrics show a poor correlation with computer vision performance, highlighting the need for newer metrics that demonstrate improved correlation. The research presented in this paper offers guidance into the enhancement of single-exposure camera-based systems for automotive applications. By addressing the balance between exposure time, image quality, and computer vision performance, the findings provide a road map for optimizing camera settings for ADAS and autonomous driving technologies, contributing to safety and performance advancements in the automotive landscape.

Background/Objectives: Radiography is an essential and low-cost diagnostic method in pulmonary medicine that is used for the early detection and monitoring of lung diseases. An adequate and consistent image quality (IQ) is crucial to ensure accurate diagnosis and effective patient management. This pilot study evaluates the feasibility and effectiveness of the International Atomic Energy Agency (IAEA)\'s remote and automated quality control (QC) methodology, which has been tested in multiple imaging centers. Methods: The data, collected between April and December 2022, included 47 longitudinal data sets from 22 digital radiographic units. Participants submitted metadata on the radiography setup, exposure parameters, and imaging modes. The database comprised 968 exposures, each representing multiple image quality parameters and metadata of image acquisition parameters. Python scripts were developed to collate, analyze, and visualize image quality data. Results: The pilot survey identified several critical issues affecting the future implementation of the IAEA method, as follows: (1) difficulty in accessing raw images due to manufacturer restrictions, (2) variability in IQ parameters even among identical X-ray systems and image acquisitions, (3) inconsistencies in phantom construction affecting IQ values, (4) vendor-dependent DICOM tag reporting, and (5) large variability in SNR values compared to other IQ metrics, making SNR less reliable for image quality assessment. Conclusions: Cross-comparisons among radiography systems must be taken with cautious because of the dependence on phantom construction and acquisition mode variations. Awareness of these factors will generate reliable and standardized quality control programs, which are crucial for accurate and fair evaluations, especially in high-frequency chest imaging.

BACKGROUND: Transthoracic echocardiography (TTE) is the primary tool for assessing left ventricular (LV) function in cardiogenic shock (CS). However, inadequate image quality often hinders it. In this retrospective study, we investigated factors associated with LV image quality in patients admitted to the intensive care unit (ICU) with ischemic CS.
RESULTS: Two critical care physicians accredited in echocardiography independently reviewed the TTEs of 100 patients admitted to our tertiary cardiac ICU with ST-elevation myocardial infarction complicated by CS between October 2016 and September 2019. Endocardial border definition (EBD) was graded for each myocardial segment of the apical 4-chamber and 2-chamber views using a conventional scoring system (1 = good, 2 = suboptimal, 3 = poor, and 4 = not possible). The biplane EBD index (EBDi) was calculated by averaging all segments from both views. An average EBDi of both observers was correlated with clinical and echocardiographic parameters. The median age was 62 years [54, 73], and 78% were males. LV ejection fraction and cardiac index (CI) medians were 29% [20, 35] and 1.93 l/min/m2 [1.40, 2.51], respectively. The median biplane EBDi was nearly suboptimal (1.833 [1.542, 2.083]). There was no correlation between EBDi and age, sex, or body mass index. However, biplane EBDi demonstrated statistically significant correlations with PaO2 (r2 = 0.066, p = 0.01), mean arterial pressure (MAP, r2 = 0.055, p = 0.03), CI (r2 = 0.105, p < 0.01), tricuspid annulus systolic velocity (RV S\', r2 = 0.092, p = 0.01), and tricuspid regurge maximum velocity (TR Vmax, r2 = 0.067, p = 0.01). In a multivariate model, only CI correlated independently with EBDi (r2 = 0.105, p < 0.01). The biplane EBDi predicted CI (area under the curve (AUC) 0.70, p = 0.001) with good sensitivity (71%) and reasonable specificity (61%).
CONCLUSIONS: The study suggests that in patients admitted to the ICU with ischemic CS, LV image quality by TTE deteriorates with the severity of shock, as indicated by CI.

X-ray imaging results in inhomogeneous irradiation of the detector and distortion of structures in the periphery of the image; yet the spatial dependency of tomosynthesis image-quality metrics has not been extensively investigated. In this study, we use virtual clinical trials to quantify the spatial dependency of lesion detectability in our lab\'s next-generation tomosynthesis (NGT) system. Two geometries were analyzed: a conventional geometry with mediolateral source motion, and a NGT geometry with T-shaped motion. Breast parenchymal texture was simulated using an open-source library with Perlin noise using 400 random seeds and three breast densities. Spherical mass lesions were inserted in the central slice of the phantoms using the voxel additive method. Image acquisition was simulated using in-house ray-tracing software and simple backprojection was performed using commercial reconstruction software. Lesion detectability with Channelized Hotelling Observers (CHOs) was analyzed using receiver operating characteristic curves to measure the detectability index (d\') at 154 unique locations for the lesions. We also divided images into three non-overlapping regions (differing in terms of distance from the chest wall). At the 0.05 level of significance, there was a statistically significant difference between the geometries in terms of d\' in one of the three regions, with the T geometry offering superior detectability. Examining all 154 lesion locations, the T geometry was found to offer lower spread (standard deviation) in d\' values throughout the image area, and superior d\' at 83 of 154 locations (53.9%). In summary, the T geometry enables superior lesion detection and mitigates anisotropies.

UNASSIGNED: We aim to develop modified clinical indication (CI)-based image quality scoring criteria (IQSC) for assessing image quality (IQ) and establishing acceptable quality doses (AQDs) in adult computed tomography (CT) examinations, based on CIs and patient sizes.
UNASSIGNED: CT images, volume CT dose index ( CTDI vol ), and dose length product (DLP) were collected retrospectively between September 2020 and September 2021 for eight common CIs from two CT scanners at a central hospital in the Kingdom of Bahrain. Using the modified CI-based IQSC and a Likert scale (0 to 4), three radiologists assessed the IQ of each examination. AQDs were then established as the median value of CTDI vol and DLP for images with an average score of 3 and compared to national diagnostic reference levels (NDRLs).
UNASSIGNED: Out of 581 examinations, 60 were excluded from the study due to average scores above or below 3. The established AQDs were lower than the NDRLs for all CIs, except AQDs / CTDI vol for oncologic follow-up for large patients (28 versus 26 mGy) in scanner A, besides abdominal pain for medium patients (16 versus 15 mGy) and large patients (34 versus 27 mGy), and diverticulitis/appendicitis for medium patients (15 versus 12 mGy) and large patients (33 versus 30 mGy) in scanner B, indicating the need for optimization.
UNASSIGNED: CI-based IQSC is crucial for IQ assessment and establishing AQDs according to patient size. It identifies stations requiring optimization of patient radiation exposure.

Intracranial vessel wall imaging (VWI), which requires both high spatial resolution and high signal-to-noise ratio (SNR), is an ideal candidate for deep learning (DL)-based image quality improvement. Conventional VWI (Conv-VWI, voxel size 0.51 × 0.51 × 0.45 mm3) and denoised super-resolution DL-VWI (0.28 × 0.28 × 0.45 mm3) of 117 patients were analyzed in this retrospective study. Quality of the images were compared qualitatively and quantitatively. Diagnostic performance for identifying potentially culprit atherosclerotic plaques, using lesion enhancement and presence of intraplaque hemorrhage (IPH), was evaluated. DL-VWI significantly outperformed Conv-VWI in all image quality ratings (all P < .001). DL-VWI demonstrated higher SNR and contrast-to-noise ratio (CNR) than Conv-VWI, both in normal walls (basilar artery; SNR 4.83 ± 1.23 vs. 3.02 ± 0.59, P < .001) and lesions (contrast-enhanced images; SNR 22.12 ± 11.68 vs. 8.33 ± 3.26, P < .001). In the assessment of 86 lesions, DL-VWI showed higher confidence of detection (4.56 ± 0.55 vs. 2.62 ± 0.77, P < .001), more concordant IPH characterization (Cohen\'s Kappa 0.85 vs. 0.59) and greater enhancement. For culprit plaque identification, IPH exhibited higher sensitivity in DL-VWI compared to Conv-VWI (70.6% vs. 23.5%) and excellent specificity (94.3% vs. 94.3%). Deep learning application of intracranial vessel wall images successfully improved the quality and resolution of the images. This aided in detecting vessel wall lesions and intraplaque hemorrhage, and in identifying potentially culprit atherosclerotic plaques.

UNASSIGNED: Spatio-temporal variability in clinical fluoroscopy and cine angiography images combined with nonlinear image processing prevents the application of traditional image quality measurements in the cardiac catheterization laboratory. We aimed to develop and validate methods to measure human observer impressions of the image quality.
UNASSIGNED: Multi-frame images of the thorax of a euthanized pig were acquired to provide an anatomical background. The detector dose was varied from 6 to 200 nGy (increments 2×), and 0.6 and 1.0 mm focal spots were used. Two coronary stents with/without 0.5 mm separation and a synthetic right coronary artery (RCA) with hemispherical defects were embedded into the background images as test objects. The quantitative observer ( n = 17 ) performance was measured using a two-alternating forced-choice test of whether stents were separated and by a count of visible right coronary artery defects. Qualitative impressions of noise, spatial resolution, and overall image quality were measured using a visual analog scale (VAS). A paired t -test and multinomial logistic regression model were used to identify statistically significant factors affecting the observer\'s impression image quality.
UNASSIGNED: The proportion of correct detection of stent separation and the number of reported right coronary artery defects changed significantly with detector dose increment in the 6 to 100 nGy ( p < 0.05 ). Although a trend favored the 0.6 versus 1.0 mm focal spot for these quantitative assessments, this was insignificant. Visual analog scale measurements changed significantly with detector dose increments in the range of 24 to 100 nGy and focal spot size ( p < 0.05 ). The application of multinomial logistic regression analysis to observer VAS scores demonstrated sensitivity matching of the paired t -test applied to quantitative observer performance measurements.
UNASSIGNED: Both quantitative and qualitative measurements of observer impression of the image quality were sensitive to image quality changes associated with changing the detector dose and focal spot size. These findings encourage future work that uses qualitative image quality measurements to assess clinical fluoroscopy and angiography image quality.

The comparative evaluation of the performance of a mobile device camera and an affordable full-frame mirrorless camera in close-range photogrammetry applications involves assessing the capabilities of these two types of cameras in capturing images for 3D measurement purposes. In this study, experiments are conducted to compare the distortion levels, the accuracy performance, and the image quality of a mobile device camera against a full-frame mirrorless camera when used in close-range photogrammetry applications in various settings. Analytical methodologies and specialized digital tools are used to evaluate the results. In the end, generalized conclusions are drawn for using each technology in close-range photogrammetry applications.

BACKGROUND: The consistency of pancreatic apparent diffusion coefficient (ADC) values and intravoxel incoherent motion (IVIM) parameter values across different magnetic resonance imaging (MRI) devices significantly impacts the patient\'s diagnosis and treatment.
OBJECTIVE: To explore consistency in image quality, ADC values, and IVIM parameter values among different MRI devices in pancreatic examinations.
METHODS: This retrospective study was approved by the local ethics committee, and informed consent was obtained from all participants. In total, 22 healthy volunteers (10 males and 12 females) aged 24-61 years (mean, 28.9 ± 2.3 years) underwent pancreatic diffusion-weighted imaging using 3.0T MRI equipment from three vendors. Two independent observers subjectively scored image quality and measured the pancreas\'s overall ADC values and signal-to-noise ratios (SNRs). Subsequently, regions of interest (ROIs) were delineated for the IVIM parameters (true diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction) using post-processing software. These ROIs were on the head, body, and tail of the pancrease. The subjective image ratings were assessed using the kappa consistency test. Intraclass correlation coefficients (ICCs) and mixed linear models were used to evaluate each device\'s quantitative parameter values. Finally, a pairwise analysis of IVIM parameter values across each device was performed using Bland-Altman plots.
RESULTS: The Kappa value for the subjective ratings of the different observers was 0.776 (P < 0.05). The ICC values for inter-observer and intra-observer agreements for the quantitative parameters were 0.803 [95% confidence interval (CI): 0.684-0.880] and 0.883 (95%CI: 0.760-0.945), respectively (P < 0.05). The ICCs for the SNR between different devices was comparable (P > 0.05), and the ICCs for the ADC values from different devices were 0.870, 0.707, and 0.808, respectively (P < 0.05). Notably, only a few statistically significant inter-device agreements were observed for different IVIM parameters, and among those, the ICC values were generally low. The mixed linear model results indicated differences (P < 0.05) in the f-value for the pancreas head, D-value for the pancreas body, and D-value for the pancreas tail obtained using different MRI machines. The Bland-Altman plots showed significant variability at some data points.
CONCLUSIONS: ADC values are consistent among different devices, but the IVIM parameters\' repeatability is moderate. Therefore, the variability in the IVIM parameter values may be associated with using different MRI machines. Thus, caution should be exercised when using IVIM parameter values to assess the pancreas.

UNASSIGNED: Abdominal radiographs remain useful in newborns. Given the high radiation sensitivity of this population, it is necessary to optimize acquisition techniques to minimize radiation exposure.
UNASSIGNED: Evaluate the effects of three additional filtrations on radiation dose and image quality in abdominal X-rays of newborns using an anthropomorphic phantom.
UNASSIGNED: Abdominal radiographs of an anthropomorphic newborn phantom were performed using acquisition parameters ranging from 55 to 70 kV and from 0.4 to 2.5 mAs, without and with three different additional filtrations: 0.1 mm copper (Cu) + 1 mm aluminum (Al), 0.2 mm copper + 1 mm aluminum, and 2 mm aluminum. For each X-ray the dose area product (DAP) was measured, the signal-to-noise ratio (SNR) was calculated, and image quality (IQ) was evaluated by two blinded radiologists using the absolute visual grading analysis (VGA) method.
UNASSIGNED: Adding an additional filtration resulted in a significant reduction in DAP, with a decrease of 42% using 2 mm Al filtration, 65% with 0.1 mm Cu + 1 mm Al filtration, and 78% with 0.2 mm Cu + 1 mm Al filtration (p < 0.01). The addition of 2 mm aluminum filtration does not significantly decrease the SNR (p = 0.31), CNR (p = 0.52) or the IQ (p = 0.12 and 0.401 for reader 1 and 2, respectively). However, adding copper-containing filtration leads to a significant decrease in, SNR, CNR and IQ.
UNASSIGNED: Adding a 2 mm Al additional filtration for abdominal radiographs in newborns can significantly reduce the radiation dose without causing a significant decrease in image quality.