OBJECTIVE: To propose a tissue- aware contrast enhancement network (T- ACEnet) for CT image enhancement and validate its accuracy in CT image organ segmentation tasks. METHODS: The original CT images were mapped to generate low dynamic grayscale images with lung and soft tissue window contrasts, and the supervised sub-network learned to recognize the optimal window width and level setting of the lung and abdominal soft tissues via the lung mask. The self-supervised sub-network then used the extreme value suppression loss function to preserve more organ edge structure information. The images generated by the T-ACEnet were fed into the segmentation network to segment multiple abdominal organs. RESULTS: The images obtained by T-ACEnet were capable of providing more window setting information in a single image, which allowed the physicians to conduct preliminary screening of the lesions. Compared with the suboptimal methods, T-ACE images achieved improvements by 0.51, 0.26, 0.10, and 14.14 in SSIM, QABF, VIFF, and PSNR metrics, respectively, with a reduced MSE by an order of magnitude. When T-ACE images were used as input for segmentation networks, the organ segmentation accuracy could be effectively improved without changing the model as compared with the original CT images. All the 5 segmentation quantitative indices were improved, with the maximum improvement of 4.16%. CONCLUSION The T-ACEnet can perceptually improve the contrast of organ tissues and provide more comprehensive and continuous diagnostic information, and the T-ACE images generated using this method can significantly improve the performance of organ segmentation tasks.
Learning ; Image Enhancement ; Tomography, X-Ray Computed

OBJECTIVE: To analyze the malfunction and maintenance process of Carestream digital X-ray machine DRX-NOVA for reference. METHODS: The fault of Carestream digital X-ray machine DRX-NOVA in 2011-2021 was summarized, the fault types were classified, and the maintenance process was summarized. RESULTS: Fault types can be divided into three categories, each of which has its own characteristics and specific solutions. CONCLUSIONS It is necessary to master the principle of equipment to repair all kinds of equipment failures. Repair the machine should be careful, comprehensive consideration of the cause of the failure. To correctly understand and analyze the operation of the machine under normal conditions, we can accurately analyze the cause of failure, so that we can really solve the problem.
X-Rays ; Radiography ; Radiographic Image Enhancement ; Equipment Failure

OBJECTIVE: Using a common DR chest radiography system to realize a long bone stitching technology. METHODS: Introduce the role of long bone stitching technology in medical diagnosis and treatment, and the principle of long bone stitching technology to make a long bone stitching radiographic device, and combine with the chest radiography system to take the long bone stitching image experiment. RESULTS: The hospitals of class Ⅱ (or more lower levels) can realize the long bone stitching technology using a common DR chest radiography system. CONCLUSIONS Using this technology can save the hospital costs, reduce the burden on patients, achieve good social and economic benefits.
Humans ; Radiographic Image Enhancement ; Radiography ; Hospitals ; Technology

This study introduced a time-delay exposure system independent of the mobile digital radiography equipment. The system consisted of lithium battery, delay control circuit, micro electric motor and related auxiliary facilities. When the starting time was reached through the delay circuit, the motor pushed out the rod to squeeze the exposure button and completed the exposure. The accessories used in this system were easy to purchase and cheap. At the same time, the technology was mature and had good compatibility. The exposure success rate was high and the exposure effect was satisfactory. This time-delay exposure system had good practicability and popularization value.
Radiographic Image Enhancement ; Technology ; Electric Power Supplies

OBJECTIVE: To propose a deep learning target detection model AM- YOLO that integrates coordinate attention and efficient attention mechanism. METHODS: Mosaic image enhancement and MixUp mixed-class enhancement were used for image preprocessing. In the target detection model YOLOv5s with One-Stage structure and modified backbone network and neck network, the maximum pooling layer of the spatial pyramid of the backbone network was replaced with a two-dimensional maximum pooling layer, and the coordinate attention mechanism and the efficient channel attention mechanism were integrated into the C3 module and the backbone network of the model, respectively. The improved model was compared with the unmodified YOLOv5s model, YOLOv3 model, YOLOv3-SPP model, and YOLOv3-tiny model for relevant algorithmic indicators in comparative experiments. RESULTS: The AM-YOLO model incorporating coordinate attention and efficient channel attention mechanism effectively improved the accuracy of melanoma recognition with also a reduced size of the model weight. This model showed significantly better performance than other models in terms of precision, recall rate and mean average precision, and its mean average precision for benign and malignant melanoma reached 92.8% and 87.1%, respectively. CONCLUSION The deep learning-based target object detection algorithm model can be applied in recognition of melanoma targets.
Humans ; Melanoma ; Skin Neoplasms ; Algorithms ; Software ; Image Enhancement

Objective To evaluate the application of two-dimensional magnetization-prepared true fast imaging with steady-state precession(2D-MP-TrueFISP)sequence in brain tumor enhancement.Methods In this study,60 cases of brain tumor patients who underwent enhanced magnetic resonance imaging of brain were scanned with 2D-MP-TrueFISP/two-dimensional spoiled gradient-recalled echo(2D-SPGR)before and after enhancement.The scores of lesions on the images of 2D-MP-TrueFISP/2D-SPGR were compared.At the same level of 2D-SPGE and 2D-MP-TrueFISP,the signal intensities(SIs)of lesions,white matter,and cerebrospinal fluid were measured before and after enhancement,and the contrast ratios(CRs)of lesions were calculated.The CRs before and after 2D-SPGR/2D-MP-TrueFISP enhancement and those between 2D-SPGR and 2D-MP-TrueFISP after enhancement were compared.Results The scores of lesions after 2D-MP-TrueFISP/2D-SPGR T1WI enhancement were 9.0(9.0,9.0)and 7.0(6.0,7.0),respectively,with significant difference(
Brain ; Brain Neoplasms/diagnostic imaging* ; Humans ; Image Enhancement ; Imaging, Three-Dimensional ; Magnetic Resonance Imaging

This paper is a summary of the three types of faults that have occurred in the recent years in the Carestream DR7500:hardware failure, software failure, and communication failure. The specific cases of three types of faults are introduced in a case-by-case basis.
Equipment Failure ; Maintenance ; Radiographic Image Enhancement

image quality and the ability to quantify myocardial blood flow (MBF) can be maintained under these conditions. This study aimed to compare the image quality, estimated MBF, and radiation dose of dynamic CTP between 2nd-DSCT and 3rd-DSCT and to evaluate whether a 10.5-cm coverage is suitable for dynamic CTP.MATERIALS AND METHODS: We retrospectively analyzed 107 patients who underwent dynamic CTP using 2nd-DSCT at 80 kV (n = 54) or 3rd-DSCT at 70 kV (n = 53). Image quality, estimated MBF, radiation dose, and coverage of left ventricular (LV) myocardium were compared.RESULTS: No significant differences were observed between 3rd-DSCT and 2nd-DSCT in contrast-to-noise ratio (37.4 ± 11.4 vs. 35.5 ± 11.2, p = 0.396). Effective radiation dose was lower with 3rd-DSCT (3.97 ± 0.92 mSv with a conversion factor of 0.017 mSv/mGy·cm) compared to 2nd-DSCT (5.49 ± 1.36 mSv, p < 0.001). Incomplete coverage was more frequent with 2nd-DSCT than with 3rd-DSCT (1.9% [1/53] vs. 56% [30/54], p < 0.001). In propensity score-matched cohorts, MBF was comparable between 3rd-DSCT and 2nd-DSCT in non-ischemic (146.2 ± 26.5 vs. 157.5 ± 34.9 mL/min/100 g, p = 0.137) as well as ischemic myocardium (92.7 ± 21.1 vs. 90.9 ± 29.7 mL/min/100 g, p = 0.876).CONCLUSION: The radiation increase inherent to the widened z-axis coverage in 3rd-DSCT can be balanced by using a tube voltage of 70 kV without compromising image quality or MBF quantification. In dynamic CTP, a z-axis coverage of 10.5 cm is sufficient to achieve complete coverage of the LV myocardium in most patients.]]>
Cardiac Imaging Techniques ; Cohort Studies ; Cytidine Triphosphate ; Humans ; Image Enhancement ; Multidetector Computed Tomography ; Myocardial Perfusion Imaging ; Myocardium ; Perfusion Imaging ; Radiation Dosage ; Radiation Exposure ; Retrospective Studies

The modifications of slices, flip angle, SAR mode and TR time are required when the SAR exceeds the limits. The scan time and image quality are affected by those. This study analyzes the SAR from the basic side. With the principle diagram of SIEMENS 1.5 T AVANTO and 3.0 T VERIO MRIS, the trouble shooting procedure of SAR problem is reached both in application and problem sides.
Algorithms ; Image Enhancement

Four-dimensional cone beam CT (4D-CBCT) imaging can provide accurate location information of real-time breathing for imaging-guided radiotherapy. How to improve the accuracy of 4D-CBCT reconstruction image is a hot topic in current studies. PICCS algorithm performs remarkably in all 4D-CBCT reconstruction algorithms based on CS theory. The improved PICCS algorithm proposed in this paper improves the prior image on the basis of the traditional PICCS algorithm. According to the location information of each phase, the corresponding prior image is constructed, which completely eliminates the motion blur of the reconstructed image caused by the mismatch of the projection data. Meanwhile, the data fidelity model of the proposed method is consistent with the traditional PICCS algorithm. The experimental results showed that the reconstructed image using the proposed method had a clearer organization boundary compared with that of images reconstructed using the traditional PICCS algorithm. This proposed method significantly reduced the motion artifact and improved the image resolution.
Algorithms ; Cone-Beam Computed Tomography ; methods ; Four-Dimensional Computed Tomography ; Humans ; Image Processing, Computer-Assisted ; Organ Motion ; Radiographic Image Enhancement ; instrumentation ; methods ; Respiration