The validity and reliability of the exposure index as a metric for estimating the radiation dose to the patient

Introduction With the introduction of digital radiography, the feedback between image quality and over-exposure has been partly lost which in some cases has led to a steady increase in dose. Over the years the introduction of exposure index (EI) has been used to resolve this phenomenon referred to as ‘dose creep’. Even though EI is often vendor specific it is always a related of the radiation exposure to the detector. Due to the nature of this relationship EI can also be used as a patient dose indicator, however this is not widely investigated in literature. Methods A total of 420 dose-area-product (DAP) and EI measurements were taken whilst varying kVp, mAs and body habitus on two different anthropomorphic phantoms (pelvis and chest). Using linear regression, the correlation between EI and DAP were examined. Additionally, two separate region of interest (ROI) placements/per phantom where examined in order to research any effect on EI. Results When dividing the data into subsets, a strong correlation between EI and DAP was shown with all R-squared values > 0.987. Comparison between the ROI placements showed a significant difference between EIs for both placements. Conclusion This research shows a clear relationship between EI and radiation dose which is dependent on a wide variety of factors such as ROI placement, body habitus. In addition, pathology and manufacturer specific EI’s are likely to be of influence as well. Implications for practice The combination of DAP and EI might be used as a patient dose indicator. However, the influencing factors as mentioned in the conclusion should be considered and examined before implementation

Convolutional neural network based encoder-decoder for efficient real-time object detection

Convolutional neural networks (CNN) are applied to a variety of computer vision problems, such as object recognition, image classification, semantic segmentation, and many others. One of the most important and difficult issues in computer vision, object detection, has attracted a lot of attention lately. Object detection validating the occurrence of the object in the picture or video and then properly locating it for recognition. However, under certain circumstances, such as when an item has issues like occlusion, distortion, or small size, there may still be subpar detection performance. This work aims to propose an efficient deep learning model with CNN and encoder decoder for efficient object detection. The proposed model is experimented on Microsoft Common Objects in Context (MS-COCO) dataset and achieved mean average precision (mAP) of about 54.1% and accuracy of 99%. The investigational outcomes amply showed that the suggested mechanism could achieve a high detection efficiency compared with the existing techniques and needed little computational resources

Factors affecting digital radiography exposure indices: are radiographers achieving the recommended levels?

Introduction With digital radiography (DR), radiographers receive immediate feedback on detector exposure in the form of the exposure index (EI). Purpose To identify whether radiographers were meeting the manufacturer-recommended EI (MREI) value ranges for routine chest, abdomen and pelvis X-ray examinations under a variety of conditions and to examine factors that impacted upon EI levels. Methods Data on 5000 adult X-ray examinations were collected, including: EI values, examination parameters, patients’ gender, dates of birth, dates and times of examinations, grid usages and the presence of metallic implants or prostheses. Descriptive statistics were used to summarise data sets and Mann–Whitney U testing was performed to establish causal agents for EI value variations. Results EI values were often outside the MREI ranges. EI value variations were identified, with significantly higher EI values recorded for female compared with male patients for all manufacturers (P ≤ 0.04), indicating higher detector exposures except for Philips direct digital radiography (DDR), where increased EI values indicated lower exposures (P=0.01). Higher EI values were also noted for the following variables: out of hours radiography (P ≤ 0.02), the absence of secondary radiation grids with Philips DDR chest X-rays (P = 0.03), younger patients with Siemens DDR chest X-rays (P < 0.0001) and higher kVp for Carestream computed radiography (CR) chest X-rays (P = 0.02). Significantly lower median EI values were demonstrated for Carestream CR chest X-rays when a metallic implant or prosthesis was present (P = 0.02). Discussion Non adherence to MREIs has been demonstrated. EI value discrepancies have been identified as being dependent on patient gender, time/day of exposure, grid usage, the presence of a metallic implants or prostheses, patient age and use of ≥ 100 kVp. The value of careful retrospective evaluation of EI databases has been highlighted

Minimization of human body responses to low frequency vibration: Application to tractors and trucks

AbstractExperimental studies of the vibrations transmitted to and tolerated by tractor and truck drivers indicate that the drivers are subjected to extremely uncomfortable levels of vertical and pitch vibrations in the frequency range of 0.5 to 11 Hz. In this study, an occupant-tractor system is modeled as a lumped parameter system. The composite model is simulated for vertical and pitch vibrational response to ground reaction by steady-state sinusoidal forcing function inputs and for transient responses by trapezoidal type of inputs. A relaxation type seat suspension located in the plane of the center of gravity of the chassis of a tractor is introduced, and the parameters of the seat suspension are determined for minimized human body responses. When these responses are compared with those of an optimized relaxation seat suspension located behind the center of gravity at the conventional location of a tractor and also with the experimental results of other investigators, it is found that the recommended location is the best among those considered. It reduces all the human body-segment responses significantly and the acceleration level to much below the eight-hour “exposure limit” tolerance curve, and thus improving riding comfort

Mimierung der vertikalen Schwingungsanregung des menschlichen Körpers in einem Traktor mittels einer Standard-Sitzaufhängung in der Schwerpunkt-Ebene

Es ist bekannt, daß bei Traktor-Fahrern verschiedene Beschwerden an der Wirbelsäule und am Stützapparat als Folge der mit geringer Frequenz (0,5—11 Hz) und großer Amplitude auftretenden Vertikalschwingungen vorkommen, die beim Fahrbetrieb auf dem Feld auftreten. Die Intensität dieser Schwingungen kann durch den Einbau von Standard-Sitz-Aufhängungen in der Schwerpunktebene des Traktors vermindert werden, wenn deren Parameter zweckmäßig gewählt werden. In dem vorliegenden Beitrag wird das System Fahrer-Traktor in einem Parameter-System mit punktförmiger Verteilung abgebildet und dieses Modell mittels Rechnersimulation in bezug auf seine Anregungen der einzelnen Körpersegmente als Folge vertikaler Schwingungsvorgaben an den Traktor-Rädern untersucht. © 1979, Walter de Gruyter. Alle Rechte vorbehalten