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20 results for “Needle Imaging”
Scanning electron microscope images of spruce needle homogenate and scanning electron microscope images of isolated small cellular particles from spruce needle homogenate
<p>Scanning electron microscope images of spruce needle homogenate and of isolated small cellular particles from spruce needle homogenate are presented. Each image is supplemented by description of the preparation of the sample and the data on the imaging technique and equipment. The data are curated by Veronika Kralj-Iglic and University of Ljubljana, Faculty of Health Sciences, Laboratory of Clinical Biophysics, and Anna Romolo, presently at University of Ljubljana, Faculty of Electrical Engineering, Laboratory of Physics, Ljubljana, Slovenia. Present address of Marko Jeran is: Department of Inorganic Chemistry and Technology, “Jožef Stefan” Institute, Ljubljana, Slovenia.</p>
Sonography display demonstrating intra-operative ultrasound imaging guidance for the localization of the foreign body (dental implant) in the soft tissues of the floor of the mouth via navigation with a spinal needle.
<p>This video demonstrates the intraoperative navigation system with using sonography to localize foreign bodies in the soft tissues of the floor of the mouth with the help of a spinal needle</p>
Tree Species Dataset consisting of Images of the Bark, Leaves or Needles
<p>This dataset consists of 3 subsets:</p> <ul> <li>Leaves of the most common Austrian broad leaf trees: Ash (25), Beech (30), Hornbeam (34), Mountain oak (22), Sycamore maple (23)</li> <li>Bark of the most common Austrian trees: Ash (34), Beech (16), Black pine (166), Fir (127), Hornbeam (42), Larch (200), Mountain oak (77), Scots pine (190), Spruce (213), Swiss stone pine (96), Sycamore maple (22)</li> <li>Needles of the most common Austrian conifers: Black pine (107), Fir (10), Larch (114), Scots pine (10), Spruce (13), Swiss stone pine (21)</li> </ul> <p>The leaf dataset consists of 134 images of five Austrian broad leaf trees which were scaled to either 800 pixel height or 600 pixel width. Every class has 25 to 34 images. While the beech, hornbeam, mountain oak and sycamore maple are complete leaves, the ash is compound, more precise a pinnate leaf.</p> <p>The dataset of bark images contains 1183 images of eleven Austrian trees. Every class has 16 to 213 images. These images were also scaled to a size of either 800 pixel height or 600 pixel width. The dataset of the black pine, fir, larch, scots pine and spruce are divided in 3 sub-classes. The first containing images of the trees when they are younger than 60, in the second one images of trees with an age of 60 to 80, and the last one with images of trees which are older than 80. These separation is necessary because especially the bark of these trees differs at different ages.</p> <p>The dataset of the needle images contains 275 of 6 Austrian conifers. Each class contains 10 to 114 images. Conifers can be divided into two classes: The first class are the fir and the spruce on which the needles grow separate on the branch and the second class are the species on which the needles grow in clusters. It can be seen that the fir, scots pine, and spruce images have been made with perfect lighting conditions, whereas the other images have been photographed in the nature.</p> <p>These datasets were gathered by employees of the ”Osterreichische ¨ Bundesforste AG“ in autumn 2009 and spring 2010.</p> <p>This database may be used for non-commercial research purpose only. If you publish material based on this database, we request you to include a reference to:</p> <p>Fiel, S. & Sablatnig, R. (2010): <em>Leaf classification using local features</em> In: Proc. of 34th annual Workshop of the Austrian Association for Pattern Recognition (AAPR), 2010, 69-74 <a href="https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/fiel-oeagm10.pdf">pdf</a></p> <p>Fiel, S. (2010): <em>Automated Identification of Tree Species from Images of the Bark, Leaves or Needles,</em> Master Thesis, Vienna University of Technology <a href="https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/tr32.pdf">pdf</a></p> <p>Version 2: added Bark.zip which is the selection of Bark images used in the paper.</p>
Multiparametric Magnetic Resonance Imaging Versus Fine Needle Aspiration Cytology for Parotid Gland Neoplasms
ClinicalTrials.gov study NCT03849482. IPD Sharing: NO. Countries: 1. Publications: 4.
In-focus and Out of focus images of the 11-needles Sorter 2 element
<p>In this dataset it is possible to observe a series of out of focus images of the Sorter 2 element, where the potentials were varied:</p> <p>-V1 is the electrostatic potential on the external needles;</p> <p>-V2 on the even needles;</p> <p>-V3 on the remaining off needles</p> <p>We are able to control the applied electrostatic potential individually on each odd needle, while the even ones are all connected and at the same potential, thanks to a custom made aperture holder by Thermofisher.</p>
Needles and Lightning Leader Dynamics Imaged with 100–200 MHz Broadband VHF Interferometry
<p>The data supports the manuscript entitled “Needles and Lightning Leader Dynamics Imaged with 100–200 MHz Broadband VHF Interferometry” that is submitted to GRL. These files can be opened by MATLAB. The data can be used freely for scientific purposes with appropriate citation.</p>
Intelligent Needle Tip Tracking Using Ultrasound Imaging for Infraclavicular Brachial Plexus Blocks
ClinicalTrials.gov study NCT03631914. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Comparison of Methods for Assisting Needle Angle Selection During Image-guided Tissue Biopsy
ClinicalTrials.gov study NCT01218854. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Virtual Path Planning for Image-guided Needle Interventions
ClinicalTrials.gov study NCT02021071. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A Study to Test Performance of Needle Placements for Neuraxial Procedures Using Tactile Imaging vs Control
ClinicalTrials.gov study NCT04796935. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation by Magnetic Resonance Imaging of Intramuscular Injections Performance in Thigh With 2 Configurations of the Needle-free Injector ZENEO®.
ClinicalTrials.gov study NCT05967013. IPD Sharing: NO. Countries: 1. Publications: 0.
3DUS Imaging of Needles in Gynecological Brachytherapy
ClinicalTrials.gov study NCT04705467. IPD Sharing: NO. Countries: 1. Publications: 0.
Image-Guided Pleural Needle Biopsy in Pleural Diseases
ClinicalTrials.gov study NCT06541470. IPD Sharing: YES. Countries: 1. Publications: 0.
Multicenter Study to Evaluate a New Robotic Device for Image-guided Percutaneous Needle Placement
ClinicalTrials.gov study NCT04230642. IPD Sharing: NO. Countries: 1. Publications: 0.
Novel Guidance Device for Image Fusion and Needle Guidance in Lung, Liver or Kidney Biopsy
ClinicalTrials.gov study NCT04039529. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of a Support Software in the Planning and Real-time Monitoring of the Insertion of Needles in Interventional Magnetic Resonance Imaging (MRI): Liver Biopsy Case
ClinicalTrials.gov study NCT02573545. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Intelligent Needle Tip Tracking Using Ultrasound Imaging for Lumbar Plexus Blocks
ClinicalTrials.gov study NCT03667898. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Performance Thresholds Evaluation by Wet Injection Quantification and Magnetic Resonance Imaging (MRI) of Subcutaneous and Intramuscular Injections (0,65ml) of Several Configurations of Needle-free De
ClinicalTrials.gov study NCT03044301. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Performance Evaluation by Magnetic Resonance Imaging (MRI) of Intramuscular Thigh Injections With 3 Configurations of Needle-free Injector (ZENEO®)
ClinicalTrials.gov study NCT03225638. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Dynamic Second Harmonic Imaging of Proton Translocation Through Water Needles in Lipid Membranes
<p>This dataset includes image/excel files for the data included in the manuscript "Dynamic Second Harmonic Imaging of Proton Translocation Through Water Needles in Lipid Membranes ". (https://pubs.acs.org/doi/full/10.1021/jacs.4c02810) </p>
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