In this contribution we discuss the possibility of designing a modified transmission X-ray microscope by using fractal zone plates (Fzps) as diffractive optical elements. In the modified transmission X-ray microscope optical layout, we first introduced a fractal zone plate as the microscope objective. Indeed, a fractal zone plate cannot only be used as an image-forming component but also as a condenser element to achieve an extended depth of field. Numerical analysis reveals that fractal zone plates and conventional Fresnel zone plates have similar imaging capabilities under different coherent illumination. Using a fractal zone plate as a condenser we also simulated axial irradiance. Results confirm that fractal zone plates can improve focusing capability with an extended depth of field. Although preliminary, these simulations clearly reveal that fractal zone plates, when available, will be of great help in microscope layouts, in particular for foreseen high-resolution applications in the "water window" as strongly required in biological research.
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http://dx.doi.org/10.1007/s00216-012-6126-0 | DOI Listing |
J Clin Med
January 2025
Surgical Services, Miami Veterans Healthcare System, Miami, FL 33125, USA.
: This study aimed to evaluate the location of retinal fractal dimension (FD) abnormalities in individuals with diabetes mellitus (DM) and hypertension (HTN) without retinopathy. The annular zone of 6 mm × 6 mm OCTA images centered on the fovea was partitioned into thin annuli and analyzed using fractal analysis to measure FDs. The cohort ( = 114) had an average age of 55.
View Article and Find Full Text PDFInt J Retina Vitreous
December 2024
Department of Biomedicine - Unit of Anatomy, Faculty of Medicine, University of Porto, Porto, Portugal.
Purpose: To assess the retinal microvasculature of Systemic Lupus Erythematosus (SLE) patients using Optical Coherence Tomography Angiography (OCTA).
Methods: Twenty adult SLE patients without disease activity and no ocular manifestations were recruited and cross-sectionally assessed. A demographically similar cohort of healthy subjects was used for comparison.
Int J Ophthalmol
September 2024
Shenzhen Eye Hospital, Jinan University, Shenzhen 518040, Guangdong Province, China.
Aim: To develop a deep learning-based model for automatic retinal vascular segmentation, analyzing and comparing parameters under diverse glucose metabolic status (normal, prediabetes, diabetes) and to assess the potential of artificial intelligence (AI) in image segmentation and retinal vascular parameters for predicting prediabetes and diabetes.
Methods: Retinal fundus photos from 200 normal individuals, 200 prediabetic patients, and 200 diabetic patients (600 eyes in total) were used. The U-Net network served as the foundational architecture for retinal artery-vein segmentation.
Transl Vis Sci Technol
August 2024
University of Houston College of Optometry, Houston, TX, USA.
Sci Total Environ
November 2024
Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China; Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China. Electronic address:
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