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.
The paper presents research results of the vibration transmitted from the steering wheel of the tractor with a 2-wheel drive to the driver’s hands. The vibration measurements were carried out on the tractor randomly chosen from the collage of agriculture / university of Baghdad. Before testing the tractor was examined and adjusted following the producer’s recommendations. The vibration levels were measured during the operation tillage at idling and at full load .The field was 31.7 m above level sea. Soil was treated at soil constant moisture (17-20 %) with depth of plowing (17 cm). During operation the weather temperature was measured (15 C) and humidity was ( 27 % ) The vibration level on the steering wheel was measured and analyzed .T
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The paper presents research results of the vibration transmitted from the steering wheel of the
tractor with a 2-wheel drive to the driver’s hands. The vibration measurements were carried out on the
tractor randomly chosen from the collage of agriculture / university of Baghdad. Before testing the
tractor was examined and adjusted following the producer’s recommendations. The vibration levels
were measured during the operation tillage at idling and at full load .The field was 3١٫٧ m above level
sea. Soil was treated at soil constant moisture (1٧-20 %) with depth of plowing (١٧ cm). During
operation the weather temperature was measured (15 C) and humidity was ( 27 % ) The vibration level
on the steering whee
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In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho
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The main objective of this study is to determine the suitable excitation wavelengths for
urine components reaching to select the suitable lasers to execute the auto fluorescence due to their
high intensities. The auto fluorescence was measured at 305, 325 and 350 nm excitation wavelengths
for eleven urine samples which were also analyzed by conventional methods (chemical and
microscopic examination). Data manipulation using Matlab package programming language showed
that urine sample with normal chemical and biological components have emission peaks which are
different from the infected urine samples. Despite the complexity of the composition of urine,
fluorescence maxima can be observed. Most likely, the peaks obser
The main objective of this study is to determine the suitable excitation wavelengths for
urine components reaching to select the suitable lasers to execute the auto fluorescence due to their
high intensities. The auto fluorescence was measured at 305, 325 and 350 nm excitation wavelengths
for eleven urine samples which were also analyzed by conventional methods (chemical and
microscopic examination). Data manipulation using Matlab package programming language showed
that urine sample with normal chemical and biological components have emission peaks which are
different from the infected urine samples. Despite the complexity of the composition of urine,
fluorescence maxima can be observed. Most likely, the peaks obser
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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