The Modulation Transfer Function () is an established means for characterizing imaging performance of X-ray radiography systems. We report on experiments using high energy, laser-driven X-ray radiography systems that assess performance using values measured with the knife-edge projection method. The broadband, hard X-ray systems under study use line-projection imaging produced by narrowing the laser-generated X-ray source with a slit. We find that good contrast resolution can be achieved (the = 0.5 at 75 m wavelength) and that this performance is reproduced on different laser facilities. We also find that the is sensitive both to the thickness of the line-projection slit and to the backing material thickness under the knife-edge. Both these sensitivities are due to a common mechanism, namely induced changes in the spectrally-averaged spatial widths of the X-ray source. The same line-projection system is also used on experimental campaigns measuring Rayleigh-Taylor instability growth by dynamically imaging sinusoidal, high micro-targets with wavelengths of 100 m or less. By applying the measured values to correct the ripple target contrast measurements, we can predict ripple growth to approximately 10% accuracy.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1063/1.5038753 | DOI Listing |
Sci Rep
December 2024
Hepatobiliary and Pancreatic Medical Treatment Center, People's Hospital of Xinjiang Uygur, Autonomous Region, Tianchi road, Urumqi, 830011, China.
With the advancement of precise hepatobiliary surgery concepts, the diagnostic and therapeutic approaches for hepatic echinococcosis have undergone significant transformations. However, whether these changes have correspondingly improved patient outcomes remains unclear. A retrospective analysis of these changes will provide crucial guidance for the prevention and treatment of hepatic echinococcosis.
View Article and Find Full Text PDFSci Rep
December 2024
School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, Life Sciences Building 85, University Road, Highfield, Southampton, SO17 1BJ, UK.
Osteoarthritis (OA) is a complex disease of cartilage characterised by joint pain, functional limitation, and reduced quality of life with affected joint movement leading to pain and limited mobility. Current methods to diagnose OA are predominantly limited to X-ray, MRI and invasive joint fluid analysis, all of which lack chemical or molecular specificity and are limited to detection of the disease at later stages. A rapid minimally invasive and non-destructive approach to disease diagnosis is a critical unmet need.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea.
Texture analysis generates image parameters from F-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT). Although some parameters correlate with tumor biology and clinical attributes, their types and implications can be complex. To overcome this limitation, pseudotime analysis was applied to texture parameters to estimate changes in individual sample characteristics, and the prognostic significance of the estimated pseudotime of primary tumors was evaluated.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Cardiology, West China Hospital of Sichuan University, 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, China.
Intracardiac echocardiography (ICE) has been used to guide radio-frequency catheter ablation (RFCA) for better catheter navigation and less radiation exposure in treating atrial fibrillation (AF). This retrospective cohort study enrolled 227 AF patients undergoing ICE- or traditional fluoroscopy (TF)-guided RFCA for AF in a tertiary hospital. ICE was used more often in patients with atrial tachycardia [odds ratio (OR) 3.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, No. 16766, Jingshi Road, Jinan, 250014, Shandong, People's Republic of China.
This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breast lesions were included, comprising 183 benign lesions and 199 malignant lesions that were collected and confirmed through clinical pathology or biopsy. The enrolled patients were randomly allocated into two groups: a training cohort and an independent test cohort, maintaining a ratio of 7:3.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!