Basics of Image Interpretation in Interventional Neuroradiology

2019 ◽  
pp. 453-462
Author(s):  
Wibke S. Müller-Forell
Keyword(s):  
Image Interpretation ◽  
Interventional Neuroradiology

Observation of biological macromolecules using various electron microscopic methods

1978 ◽  
Vol 36 (2) ◽  
pp. 170-171
Author(s):  
Mitsuo Ohtsuki ◽  
Michael Sogard
Keyword(s):  
Electron Microscope ◽  
Phase Contrast ◽  
Image Interpretation ◽  
Density Lipoprotein ◽  
Biological Macromolecules ◽  
Contrast Effects ◽  
Biological Structure ◽  
Electron Microscopic ◽  
Structural Investigations ◽  
Staining Techniques

Structural investigations of biological macromolecules commonly employ CTEM with negative staining techniques. Difficulties in valid image interpretation arise, however, due to problems such as variability in thickness and degree of penetration of the staining agent, noise from the supporting film, and artifacts from defocus phase contrast effects. In order to determine the effects of these variables on biological structure, as seen by the electron microscope, negative stained macromolecules of high density lipoprotein-3 (HDL3) from human serum were analyzed with both CTEM and STEM, and results were then compared with CTEM micrographs of freeze-etched HDL3. In addition, we altered the structure of this molecule by digesting away its phospholipid component with phospholipase A2 and look for consistent changes in structure.

Simulated Dark-Field Electron Micrographs of Point Defects and Organometallics

1975 ◽  
Vol 33 ◽  
pp. 200-201
Author(s):  
William Krakow
Keyword(s):  
Electron Micrographs ◽  
Point Defects ◽  
Structure Determination ◽  
Atomic Structure ◽  
Image Interpretation ◽  
Dark Field ◽  
Field Electron ◽  
Dark Field Microscopy ◽  
Dark Field Electron

Tilted beam dark-field microscopy has been applied to atomic structure determination in perfect crystals, several synthesized molecules with heavy atcm markers and in the study of displaced atoms in crystals. Interpretation of this information in terms of atom positions and atom correlations is not straightforward. Therefore, calculated dark-field images can be an invaluable aid in image interpretation.

A method for direct measurement of specimen noise in HREM images

1993 ◽  
Vol 51 ◽  
pp. 458-459
Author(s):  
Sidnei Paciornik ◽  
Roar Kilaas ◽  
Ulrich Dahmen ◽  
Michael Adrian O'Keefe
Keyword(s):  
Random Noise ◽  
Image Interpretation ◽  
Thin Foil ◽  
High Resolution Electron Microscopy ◽  
Black Dot ◽  
Atomic Column ◽  
Amorphous Oxide ◽  
Resolution Electron ◽  
Imaging Conditions ◽  
Image Simulations

High resolution electron microscopy (HREM) is a primary tool for studying the atomic structure of defects in crystals. However, the quantitative analysis of defect structures is often seriously limited by specimen noise due to contamination or oxide layers on the surfaces of a thin foil.For simple monatomic structures such as fcc or bcc metals observed in directions where the crystal projects into well-separated atomic columns, HREM image interpretation is relatively simple: under weak phase object, Scherzer imaging conditions, each atomic column is imaged as a black dot. Variations in intensity and position of individual image dots can be due to variations in composition or location of atomic columns. Unfortunately, both types of variation may also arise from random noise superimposed on the periodic image due to an amorphous oxide or contamination film on the surfaces of the thin foil. For example, image simulations have shown that a layer of amorphous oxide (random noise) on the surfaces of a thin foil of perfect crystalline Si can lead to significant shifts in image intensities and centroid positions for individual atomic columns.

Molecular Views of Ice-Embedded Lumbricus Terrestris Erythrocruorin Obtained By Invariant Classification

1990 ◽  
Vol 48 (1) ◽  
pp. 450-451
Author(s):  
Michael schatz ◽  
Joachim Jäger ◽  
Marin van Heel
Keyword(s):  
Image Interpretation ◽  
Lumbricus Terrestris ◽  
Reference Image ◽  
Large Set ◽  
Multivariate Statistical ◽  
Data Set ◽  
Low Contrast ◽  
Negative Stain ◽  
Reference Images ◽  
Statistical Resolution

Lumbricus terrestris erythrocruorin is a giant oxygen-transporting macromolecule in the blood of the common earth worm (worm "hemoglobin"). In our current study, we use specimens (kindly provided by Drs W.E. Royer and W.A. Hendrickson) embedded in vitreous ice (1) to avoid artefacts encountered with the negative stain preparation technigue used in previous studies (2-4).Although the molecular structure is well preserved in vitreous ice, the low contrast and high noise level in the micrographs represent a serious problem in image interpretation. Moreover, the molecules can exhibit many different orientations relative to the object plane of the microscope in this type of preparation. Existing techniques of analysis requiring alignment of the molecular views relative to one or more reference images often thus yield unsatisfactory results.We use a new method in which first rotation-, translation- and mirror invariant functions (5) are derived from the large set of input images, which functions are subsequently classified automatically using multivariate statistical techniques (6). The different molecular views in the data set can therewith be found unbiasedly (5). Within each class, all images are aligned relative to that member of the class which contributes least to the classes′ internal variance (6). This reference image is thus the most typical member of the class. Finally the aligned images from each class are averaged resulting in molecular views with enhanced statistical resolution.

Interventional Neuroradiology for Skull Base Pathologies

Skull Base ◽  
2009 ◽  
Vol 19 (S 02) ◽  
Author(s):  
A. Valavanis
Keyword(s):  
Skull Base ◽  
Interventional Neuroradiology

Pemetaan Pulau Kecil Gelasa Kabupaten Bangka Tengah

2019 ◽  
Vol 2 (1) ◽  
pp. 11-14
Author(s):  
Wahyu Adi
Keyword(s):  
Coral Reefs ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Interpretation ◽  
Vegetation Coverage ◽  
Small Island ◽  
Shallow Waters ◽  
Small Islands ◽  
Seagrass Beds ◽  
Cover Density

Pulau Kecil Gelasa merupakan daerah yang belum banyak diteliti. Pemetaan ekosistem di pulau kecil dilakukan dengan bantuan citra Advanced Land Observing Satellite (ALOS). Penelitian terdahulu diketahui bahwa ALOS memiliki kemampuan memetakan terumbu karang dan padang lamun di perairan dangkal serta mampu memetakan kerapatan penutupan vegetasi. Metode interpretasi citra menggunakan alogaritma indeks vegetasi pada citra ALOS yaitu NDVI (Normalized Difference Vegetation Index), serta pendekatan Lyzengga untuk mengkoreksi kolom perairan. Hasil penelitian didapatkan luasan Padang Lamun di perairan dangkal 41,99 Ha, luasan Terumbu Karang 125,57 Ha. Hasil NDVI di daratan/ pulau kecil Gelasa untuk Vegetasi Rapat seluas 47,62 Ha; luasan penutupan Vegetasi Sedang 105,86 Ha; dan penutupan Vegetasi Jarang adalah 34,24 Ha.   Small Island Gelasa rarely studied. Mapping ecosystems on small islands with the image of Advanced Land Observing Satellite (ALOS). Previous research has found that ALOS has the ability to map coral reefs and seagrass beds in shallow water, and is able to map vegetation cover density. The method of image interpretation uses the vegetation index algorithm in the ALOS image, NDVI (Normalized Difference Vegetation Index), and the Lyzengga approach to correct the water column. The results of the study were obtained in the area of Seagrass Padang in the shallow waters of 41.99 ha, the area of coral reefs was 125.57 ha. NDVI results on land / small islands Gelasa for dense vegetation of 47.62 ha; area of Medium Vegetation coverage 105.86 Ha; and the coverage of Rare Vegetation is 34.24 Ha.

Methodology for TEM Analysis of Barrier Profiles

2002 ◽  
Author(s):  
Tan-Chen Lee ◽  
Jui-Yen Huang ◽  
Li-Chien Chen ◽  
Ruey-Lian Hwang ◽  
David Su
Keyword(s):  
Sample Preparation ◽  
Profile Analysis ◽  
Image Interpretation ◽  
Sample Thickness ◽  
Image Resolution ◽  
Specimen Preparation ◽  
Tem Analysis ◽  
Preparation Methods ◽  
High Image Resolution ◽  
Common Technique

Abstract Device shrinkage has resulted in thinner barriers and smaller vias. Transmission Electron Microscopy (TEM) has become a common technique for barrier profile analysis because of its high image resolution. TEM sample preparation and image interpretation becomes difficult when the size of the small cylindrical via is close to the TEM sample thickness. Effects of different sample thickness and specimen preparation methods, therefore, have been investigated. An automatic FIB program has been shown to be useful in via sample preparation. Techniques for imaging a TEM specimen will be discussed in the paper. Conventional TEM bright field (BF) image is adequate to examine the barrieronly via; however, other techniques are more suitable for a Cu filled via.

Stacked Die Analysis Using C-mode Scanning Acoustic Microscope

2005 ◽  
Author(s):  
Li Na ◽  
Jawed Khan ◽  
Lonnie Adams
Keyword(s):  
Data Acquisition ◽  
Image Interpretation ◽  
Acoustic Microscopy ◽  
Scanning Acoustic Microscopy ◽  
Acoustic Microscope ◽  
Analysis Mode ◽  
Scanning Acoustic Microscope

Abstract For stacked die package delamination inspection using C-mode acoustic microscope, traditional interface and thorough scan techniques cannot give enough of information when the delamination occurs in multi-interfaces, and echoes from adjacent interfaces are not sufficiently separated from each other. A thinner thickness in the stacked-die package could complicate C-mode scanning acoustic microscopy (CSAM) analysis and sometimes may lead to false interpretations. The first objective of this paper is to briefly explain the CSAM mechanism. Based on that, some of the drawbacks of current settings in detecting the delamination for stacked-die packages are presented. The last objective is to introduce quantitative B-scan analysis mode (Q-BAM) and Zip-Slice technologies in order to better understand and improve the reliability of detecting the delamination in stacked-die packages. Therefore, a large portion of this paper focuses on the Q-BAM and Zip-Slice data acquisition and image interpretation.

Sign in / Sign up

Export Citation Format

Share Document