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A hand-held hybrid gamma-near-infrared fluorescence imaging camera
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Objectives: Recently, there have been important advances in the clinical application of targeted hybrid near-infrared (NIR) fluorescent-radioactive tracers. ICG-99mTc-nanocolloid, for example, is already being used by some centres for sentinel lymph node biopsy in head and neck cancer. The radioactive component allows imaging at depths which would not be possible with NIR alone and, once exposed, the NIR fluorescence reporter can be imaged at very high resolution. Gamma detection is currently carried out with a separate hand-held gamma camera or with a non-imaging probe. Visualisation of NIR fluorescence during surgery requires a dedicated NIR camera, several of which are available commercially. We describe a novel hand-held hybrid NIR-gamma small field of view camera, capable of displaying co-aligned images from both modalities, which can be fused into one image or viewed separately. This study is a preliminary investigation of the performance of the fluorescence component of this camera, including phantom studies and first images from a preclinical pilot study. Methods: The hybrid camera consists of a 1500 µm thick thallium doped caesium iodide columnar (CsI:Tl) scintillator coupled to an electron multiplying charged coupled device (EMCCD). A 1.0mm diameter tungsten pinhole collimator gives a 40mm x 40mm nominal field of view for an 8mm x 8mm CCD detection area. A fluorescence camera was aligned to provide the same field of view as the gamma camera with an LED ring as the excitation source. The performance of the fluorescence imaging was quantified in this study for the fluorophores ICG and IRDye800CW (CW800) using a range of bespoke phantom experiments. In vivo images were also obtained from a preclinical study of a targeted hybrid tracer (cRGD-CW800-TCO + TCO-DOTA-111In) in mice with HT29 colorectal cancer xenografts. RESULTS AND CONCLUSION: The portable hybrid camera prototype has been shown to successfully image dual NIR-gamma tracers using both in vitro and in vivo experimental models. With further development, this camera could be used intraoperatively, offering the benefits of gamma imaging at depth in tissues and high resolution surface NIR fluorescence imaging in a single imaging system.

Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Assessment of image quality of cervical spine complications using Three Magnetic Resonance Imaging Sequences
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Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference

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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Diagnostic Evaluation of Uterine Artery Doppler Imaging for the Prediction of Early Abnormal Pregnancy
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Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy. Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when appropriate, was

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Publication Date
Tue Jun 30 2015
Journal Name
Al-kindy College Medical Journal
Compound fractures of the hand metacarpals and phalanges treated by using mini-external fixator
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Background: A review of articles of method in treating compound phalangeal fractures by using mini-external fixator, elaborating the anatomy, mechanics, modalities of treatment, and complications of these types of fractures. Also, it compares between different studies regarding the functional results and final outcome. External fixation of phalangeal fractures is a good method for osteo synthesis in certain situations. The simplicity of the surgical procedure and the minimal disruption of the normal bone architecture also make it appealing.Objectives: Evaluating the functional results of the use of mini-external fixator for the treatment of compound fractures of phalangeal bones of the hand.Method: Our study consists of 15 patients, 12 w

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Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

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Publication Date
Tue Oct 18 2022
Journal Name
Applied Sciences
The Influence of Flight Direction and Camera Orientation on the Quality Products of UAV-Based SfM-Photogrammetry
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Unmanned aerial vehicles (UAVs) can provide valuable spatial information products for many projects across a wide range of applications. One of the major challenges in this discipline is the quality of positioning accuracy of the resulting mapping products in professional photogrammetric projects. This is especially true when using low-cost UAV systems equipped with GNSS receivers for navigation. In this study, the influence of UAV flight direction and camera orientation on positioning accuracy in an urban area on the west bank of the Euphrates river in Iraq was investigated. Positioning accuracy was tested in this study with different flight directions and camera orientation settings using a UAV autopilot app (Pix4Dcapture software

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Publication Date
Sat Mar 31 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Synthesis of Nano Crystalline Gamma Alumina from Waste Cans
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In the present study waste aluminium cans were recycled and converted to produce alumina catalyst. These cans contain more than 98% aluminum oxide in their structure and were successfully synthesized to produce nano sized gamma alumina under mild conditions. A comprehensive study was carried out in order to examine the effect of several important parameters on maximum yield of alumina that can be produced. These parameters were reactants mole ratios (1.5, 1.5, 2, 3, 4 and 5), sodium hydroxide concentrations (10, 20, 30, 40, 50 and 55%) and weights of aluminum cans (2, 4, 6, 8 and 10 g). The compositions of alumina solution were determined by Atomic absorption spectroscopy (AAS); and maximum yield of alumina solution was 96.3% obtain

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Publication Date
Sat Jun 29 2013
Journal Name
Journal Of Statistics Applications & Probability
Analyzing Skewed Data with the Epsilon Skew Gamma distribution
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A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Gamma irradiation effect on characterization of MoO3 nanostructures films
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Publication Date
Thu Dec 28 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Determining the Concentrations of Elements in Tobacco Selected in Iraqi Markets Using X-Ray Fluorescence Technique
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  X-rays fluorescence technology was used  to measure the concentrations of trace and toxic elements in tobacco smoke. One sample local and eight samples were imported selected from Iraqi markets. The results proved that tobaccos contain few concentrations of element (calcium, potassium, sodium, manganese, magnesium, chlorine, and sulfur), trace concentrations of element (aluminum, vanadium, iron, cobalt, nickel, copper and zinc), and toxic concentrations of element (arsenic, selenium, bromine, antimony, cadmium, mercury and lead). Results are proved the concentrations of elements of samples are lower levels with the other countries in few element like (calcium, potassium, sodium and manganese), while the other elements were hi

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
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Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

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