Formation of ionized excited states from the loss of the metastable electron in the noble gas atoms

Ionized excited states formed by loss of metastable electron in rare gas atom

Excitation cross section for some of the doubly ionized states of argon, neon and krypton by fast electrons

Excitation cross section for doubly ionized states of argon, neon, and krypton by fast electron

Lifetime and transition probabilities of Np4 - /n plus 1/ p states of Ne 2, A 2, and Kr 2

Calculation of lifetime and transition probability of p-excited states of neon, argon, and krypto

Approximate transition probabilities and lifetime of some of the excited states of neutral iodine

Transition probabilities and lifetimes of energy states of neutral iodin

Investigation of a Few Simple Molecular Gases as a Possible Molecular Laser Material

Energy levels of simple molecular gases for possible molecular laser materia

High Sensitive FBG Based Muscular Strain Sensor

Assessment of biomechanical behavior of human musculoskeletal structure is essential to recognize bone diseases and to design proper medical devices.  The skeleton system basically adapts to mechanical loadings. Thus, monitoring the bone deformation under load is of great importance to attain better analysis and interpretation.  In recent years, Fiber Bragg Grating sensing devices have been developed and used to monitor strain and temperature of skeleton system.  In this work a Fiber Bragg Grating sensor is designed holding a 1.54 pmµε-1 axial strain sensitivity which is almost 30% higher than the one achieved so far.  The improvement in sensitivity is achieved by adjusting single-mode optical fiber parameters of the structure

Automated choroidal segmentation of 1060 nm OCT in healthy and pathologic eyes using a statistical model

A two stage statistical model based on texture and shape for fully automatic choroidal segmentation of normal and pathologic eyes obtained by a 1060 nm optical coherence tomography (OCT) system is developed. A novel dynamic programming approach is implemented to determine location of the retinal pigment epithelium/ Bruch’s membrane /choriocapillaris (RBC) boundary. The choroid–sclera interface (CSI) is segmented using a statistical model. The algorithm is robust even in presence of speckle noise, low signal (thick choroid), retinal pigment epithelium (RPE) detachments and atrophy, drusen, shadowing and other artifacts. Evaluation against a set of 871 manually segmented cross-sectional scans from 12 eyes achieves an average error rate of 13%, computed per tomogram as a ratio of incorrectly classified pixels and the total layer surface. For the first time a fully automatic choroidal segmentation algorithm is successfully applied to a wide range of clinical volumetric OCT data

Retinal Nerve Fiber Layer Segmentation on FD-OCT Scans of Normal Subjects and Glaucoma Patients

Automated measurements of the retinal nerve fiber layer thickness on circular OCT B-Scans provide physicians additional parameters for glaucoma diagnosis. We propose a novel retinal nerve fiber layer segmentation algorithm for frequency domain data that can be applied on scans from both normal healthy subjects, as well as glaucoma patients, using the same set of parameters. In addition, the algorithm remains almost unaffected by image quality. The main part of the segmentation process is based on the minimization of an energy function consisting of gradient and local smoothing terms. A quantitative evaluation comparing the automated segmentation results to manually corrected segmentations from three reviewers is performed. A total of 72 scans from glaucoma patients and 132 scans from normal subjects, all from different persons, composed the database for the evaluation of the segmentation algorithm. A mean absolute error per A-Scan of 2.9 µm was achieved on glaucomatous eyes, and 3.6 µm on healthy eyes. The mean absolute segmentation error over all A-Scans lies below 10 µm on 95.1% of the images. Thus our approach provides a reliable tool for extracting diagnostic relevant parameters from OCT B-Scans for glaucoma diagnosis

FloatingCanvas: quantification of 3D retinal structures from spectral-domain optical coherence tomography

Spectral-domain optical coherence tomography (SD-OCT) provides volumetric images of retinal structures with unprecedented detail. Accurate segmentation algorithms and feature quantification in these images, however, are needed to realize the full potential of SD-OCT. The fully automated segmentation algorithm, FloatingCanvas, serves this purpose and performs a volumetric segmentation of retinal tissue layers in three-dimensional image volume acquired around the optic nerve head without requiring any pre-processing. The reconstructed layers are analysed to extract features such as blood vessels and retinal nerve fibre layer thickness. Findings from images obtained with the RTVue-100 SD-OCT (Optovue, Fremont, CA, USA) indicate that FloatingCanvas is computationally efficient and is robust to the noise and low contrast in the images. The FloatingCanvas segmentation demonstrated good agreement with the human manual grading. The retinal nerve fibre layer thickness maps obtained with this method are clinically realistic and highly reproducible compared with time-domain StratusOCT™

Wavelet denoising of multiframe optical coherence tomography data

We introduce a novel speckle noise reduction algorithm for OCT images. Contrary to present approaches, the algorithm does not rely on simple averaging of multiple image frames or denoising on the final averaged image. Instead it uses wavelet decompositions of the single frames for a local noise and structure estimation. Based on this analysis, the wavelet detail coefficients are weighted, averaged and reconstructed. At a signal-to-noise gain at about 100% we observe only a minor sharpness decrease, as measured by a full-width-half-maximum reduction of 10.5%. While a similar signal-to-noise gain would require averaging of 29 frames, we achieve this result using only 8 frames as input to the algorithm. A possible application of the proposed algorithm is preprocessing in retinal structure segmentation algorithms, to allow a better differentiation between real tissue information and unwanted speckle noise