Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Analysis of nanoparticle Transmission Electron Microscopy data using a public-domain image-processing program, Image
Date
2006-01-01
Author
Woehrle, GH
Hutchison, JE
Özkar, Saim
Finke, RG
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
198
views
0
downloads
Cite This
The need to easily and quickly count larger numbers of nanoparticles, in order to obtain statistically useful size and size-distribution data, is addressed via the use of a readily available, free, public-domain program for particle counting, NIH-Image (and 2 others derived from it, Scion Image and Image J), collectively referred to herein as Image. The best protocols that we have found useful for the use of Image are reported; both appropriate as well as problematic applications of Image are then illustrated with a series of TEM images of Ir(0), Pd(0) and Au(0) nanoclusters. Methods to detect and image nanoclusters with sub-1-nm core diameters are reported and illustrated in the literature with An nanoclusters, an important problem since the literature indicates that subnanometer An nanoclusters are often present, but undetected. A list of suggestions and caveats for the appropriate use of Image is also provided, since this contribution is directed at first-time users who are not presently using nanoparticle imaging software. The reader is also reminded of several, well-known caveats for the use of TEM in obtaining size data for nanostructures. Overall, Image is a free, public-domain program that is useful for the rapid counting of large numbers of particles.
Subject Keywords
Nanoparticles
,
Particle size distributions
,
Transmission electron microscopy
,
Image analysis
,
Image (NIH-Image, Scion Image, Image J)
,
Histograms
URI
https://hdl.handle.net/11511/55747
Journal
TURKISH JOURNAL OF CHEMISTRY
Collections
Department of Chemistry, Article
Suggestions
OpenMETU
Core
Alignment of uncalibrated images for multi-view classification
Arık, Sercan Ömer; Vural, Elif; Frossard, Pascal (2011-12-29)
Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of im...
Design and implementation of a novel visual analysis system for image clasiffication
Altintakan, Ümit Lütfü; Yazıcı, Adnan; Körpeoğlu, İbrahim; Department of Computer Engineering (2013)
Possibilities offered by the technology to create, share and disseminate image and video data have resulted in a rapid increase in the available visual data. However, the data is useless unless it is effectively accessed, which necessitates the semantic analysis of visual data. In this dissertation, we present a novel visual analysis system along with its application to image classification problem. We aim to address the challenges in the area originated from the semantic gap, and to facilitate the research...
Implement of three segmentation algorithms for CT images of torso
Öz, Sinan; Serinağaoğlu Doğrusöz, Yeşim; Department of Electrical and Electronics Engineering (2011)
Many practical applications in the field of medical image processing require valid and reliable segmentation of images. In this dissertation, we propose three different semi-automatic segmentation frameworks for 2D-upper torso medical images to construct 3D geometric model of the torso structures. In the first framework, an extended version of the Otsu’s method for three level thresholding and a recursive connected component algorithm are combined. The segmentation process is accomplished by first using Ext...
Capturing and detection of MCF-7 breast cancer cells with a CMOS image sensor
Musayev, Javid; Altiner, Caglar; Adiguzel, Yekbun; Külah, Haluk; Eminoglu, Selim; Akın, Tayfun (2014-08-15)
This paper presents a CMOS image sensor with a 32 x 32 pixel array for cell capture, detection, and quantification. Pixels measuring 15 pm x 15 mu m have a modified structure, suitable for post-CMOS electroless gold plating, which enables surface activation for cell capture without the need for any intermediate layer. This structure also increases the detection probability of captured cells, even when cells are much smaller than the pixel, owing to a special light mask implemented on pixels. Cells as small ...
Superpixel based image sequence representation and motion estimation
İnce, Kutalmış Gökalp; Alatan, Abdullah Aydın; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2017)
In this study a superpixel based representation of image sequences is proposed. For superpixel extraction, a novel gradient ascent approach, in which spatial and spectral statistics are utilized to obtain an optimal Bayesian classifier for pixel to superpixel label assignment, is proposed. Utilization of the spectral and spatial statistics reduce the dependency on user selected global parameters, while increasing the robustness and adaptability. Proposed Local Adaptive Superpixels (LASP) approach exploits he...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. Woehrle, J. Hutchison, S. Özkar, and R. Finke, “Analysis of nanoparticle Transmission Electron Microscopy data using a public-domain image-processing program, Image,”
TURKISH JOURNAL OF CHEMISTRY
, pp. 1–13, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55747.