39 research outputs found
High-fidelity quantitative differential phase contrast deconvolution using dark-field sparse prior
Differential phase contrast (DPC) imaging plays an important role in the family of quantitative phase measurement. However, the reconstruction algorithm for quantitative DPC (qDPC) imaging is not yet optimized, as it does not incorporate the inborn properties of qDPC imaging. In this research, we propose a simple but effective image prior, the dark-field sparse prior (DSP), to facilitate the phase reconstruction quality for all DPC-based phase reconstruction algorithms. The DSP is based on the key observation that most pixel values for an idea differential phase contrast image are zeros since the subtraction of two images under anti-symmetric illumination cancels all background components. With this DSP prior, we formed a new cost function in which L0-norm was used to represent the DSP. Further, we developed the algorithm based on the Half Quadratic Splitting to solve this NP-hard L0-norm problem. We tested our new model on both simulated and experimental data and compare it against state-of-The-Art (SOTA) methods including L2-norm and total variation regularizations. Results show that our proposed model is superior in terms of phase reconstruction quality and implementation efficiency, which significantly increases the experimental robustness, while maintaining the data fidelity. In general, the DSP supports high-fidelity qDPC reconstruction without any modification of the optical system, which simplifies the system complexity and benefit all qDPC applications
Geodesic Tracking of Retinal Vascular Trees with Optical and TV-Flow Enhancement in SE(2)
Retinal images are often used to examine the vascular system in a non-invasive way. Studying the behavior of the vasculature on the retina allows for noninvasive diagnosis of several diseases as these vessels and their behavior are representative of the behavior of vessels throughout the human body. For early diagnosis and analysis of diseases, it is important to compare and analyze the complex vasculature in retinal images automatically. In previous work, PDE-based geometric tracking and PDE-based enhancements in the homogeneous space of positions and orientations have been studied and turned out to be useful when dealing with complex structures (crossing of blood vessels in particular). In this article, we propose a single new, more effective, Finsler function that integrates the strength of these two PDE-based approaches and additionally accounts for a number of optical effects (dehazing and illumination in particular). The results greatly improve both the previous left-invariant models and a recent data-driven model, when applied to real clinical and highly challenging images. Moreover, we show clear advantages of each module in our new single Finsler geometrical method
Understanding the clinical and molecular basis of thyroid orbitopathy:a review of recent evidence
Thyroid eye disease (TED) is an autoimmune orbital inflammatory disease which ranges from mild to severe. Tissue remodeling, fibrosis and fat proliferation cause changes in the orbital tissues which can affect esthetics and visual function. In its severe form, it is sight threatening, debilitating, and disfiguring and may lead to social stigma, the embarrassment about which has an impact on the quality of life of those affected and the family members. The pathogenesis of TED, which is influenced by genetic, immunological, and environmental factors, is complex and not fully elucidated. However, it remains unknown what factors determine the severity of the disease. Recent research has revealed a number of diagnostic and prognostic biomarkers of this disease. In this overview of TED, we focus on new insights and perspectives regarding biological agents that may provide a basis for new treatment modalities.</p
Evaluation of a visual acuity eHealth tool in patients with cataract
To validate the Easee web-based tool for the assessment of visual acuity in patients who underwent cataract surgery.Setting:University Eye Clinic Maastricht, Maastricht, the Netherlands.Design:Prospective method comparison study.Methods:Subjects aged between 18 and 69 years who underwent cataract surgery on 1 or both eyes at the Maastricht University Medical Center+ were eligible to participate in this study. The uncorrected (UDVA) and corrected distance visual acuity (CDVA) assessments were performed using the web-based tool (index test) and conventional ETDRS and Snellen charts (reference tests). The outcomes of the different tests were expressed in logMAR, and a difference of <0.15 logMAR was considered clinically acceptable.Results:46 subjects with 75 operated eyes were included in this study. The difference of the UDVA between the web-based tool and ETDRS or Snellen was -0.05 ± 0.10 logMAR (P <.001 [0.15; -0.26]) and -0.04 ± 0.15 logMAR (P =.018 [0.24; -0.33]), respectively. For the CDVA, these differences were -0.04 ± 0.08 logMAR (P <.001 [0.13; -0.21]) and -0.07 ± 0.10 logMAR (P <.001 [0.13; -0.27]), respectively. The Pearson correlation coefficients between the web-based tool and ETDRS were maximally 0.94 and compared with Snellen 0.92. In total, 73% to 88% of the visual acuity measurement differences were within 0.15 logMAR.Conclusions:The web-based tool was validated for the assessment of visual acuity in patients who underwent cataract surgery and showed clinically acceptable outcomes in up to 88% of patients. Most of the participants had a positive attitude toward the web-based tool, which requires basic digital skills
XEN® Gel Stent compared to PRESERFLO™ MicroShunt implantation for primary open-angle glaucoma: two-year results
Purpose: To evaluate the long-term efficacy and safety of two minimally invasive glaucoma surgery implants with a subconjunctival drainage approach: the XEN45 Gel Stent® (Xen) implant and the PRESERFLO™ MicroShunt (MicroShunt). Methods: Retrospective comparative case series of primary open-angle glaucoma (POAG) patients with at least 6 months of follow-up after a MicroShunt or Xen implantation augmented with mitomycin C. Results: Forty-one eyes of 31 patients underwent Xen implantation, and 41 eyes of 33 patients, MicroShunt implantation. Baseline characteristics were similar, except for more combined surgeries with phacoemulsification in the Xen group (37% vs. 2%). Mean baseline IOP ± standard deviation dropped from 19.2 ± 4.4 to 13.8 ± 3.8 mmHg (n = 26) in the Xen group and from 20.1 ± 5.0 to 12.1 ± 3.5 (n = 14) in the MicroShunt group at 24 months of follow-up (p = 0.19, t-test). The number of IOP-lowering medications dropped from 2.5 ± 1.4 to 0.9 ± 1.2 in the Xen group and from 2.3 ± 1.5 to 0.7 ± 1.1 in the MicroShunt group. The probability of qualified success was 73% and 79% at 24 months of follow-up for the Xen and MicroShunt groups, respectively. Postoperative complications were usually mild and self-limiting. The number of bleb needling and secondary glaucoma surgery procedures was similar in both groups; however, in the Xen group more additional MicroPulse® transscleral cyclophotocoagulation procedures were performed. Conclusion: Xen Gel Stent and PreserFlo MicroShunt implantations achieved comparable results in POAG eyes in terms of IOP-lowering and surgical success, with a similar high safety profile
Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study
Type 2 Diabetes (T2D) is a chronic metabolic disorder that can lead to
blindness and cardiovascular disease. Information about early stage T2D might
be present in retinal fundus images, but to what extent these images can be
used for a screening setting is still unknown. In this study, deep neural
networks were employed to differentiate between fundus images from individuals
with and without T2D. We investigated three methods to achieve high
classification performance, measured by the area under the receiver operating
curve (ROC-AUC). A multi-target learning approach to simultaneously output
retinal biomarkers as well as T2D works best (AUC = 0.746 [0.001]).
Furthermore, the classification performance can be improved when images with
high prediction uncertainty are referred to a specialist. We also show that the
combination of images of the left and right eye per individual can further
improve the classification performance (AUC = 0.758 [0.003]), using a
simple averaging approach. The results are promising, suggesting the
feasibility of screening for T2D from retinal fundus images.Comment: to be published in the proceeding of SPIE - Medical Imaging 2020, 6
pages, 1 figur
Reduced corneal nerve fibre length in prediabetes and type 2 diabetes: The Maastricht Study
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Harnessing abruptly auto-defocusing beam to enhance the Raman signal in aqueous humor: A simulation analysis
Raman aqueous humor detection provides a non-invasive, molecular-level approach for ingredient analysis within aqueous humor. However, current Raman aqueous humor applications are facing low signal-to-noise levels due to the trade-off between laser power and laser safety. In order to increase Raman signal while guaranteeing laser safety, in the research, we propose to use the abruptly auto-defocusing (AADF) beam as the illumination source for Raman aqueous humor spectroscopy. The ray-tracing sketch together with the propagation simulation of AADF shows its evolution within the aqueous humor. The intensity distributions are analyzed with and without the impact of corneal refraction. Results show that the efficiency of AADF is higher than the conventional focused Gaussian beam (FGB) method with center blocked. The peak value of the Raman signal intensity acquired using the AADF method is about 6 times larger than that of an FGB
A survery of Nematode infection in Oreochromis niloticus[L] on Lake Kyoga
A survey of Nematodes infection on L.Kyoga UgandaDepartment of Zoology Maker ere Universit