Hyperspectral holographic imaging of brain tissues using swept-source diffraction phase microscopy

2014 ◽  
Author(s):  
Shinwha Lee ◽  
EekSung Lee ◽  
Jaehwang Jeong ◽  
HyunJoo Park ◽  
Yong Jeong ◽  
...  
Keyword(s):  
Swept Source ◽  
Phase Microscopy ◽  
Holographic Imaging ◽  
Brain Tissues

Full-field swept-source phase microscopy

2006 ◽  
Author(s):  
Marinko Sarunic ◽  
Seth Weinberg ◽  
Audrey Ellerbee ◽  
Brian Applegate ◽  
Joseph Izatt
Keyword(s):  
Swept Source ◽  
Full Field ◽  
Phase Microscopy ◽  
Source Phase

Full-field swept-source phase microscopy

2006 ◽  
Vol 31 (10) ◽  
pp. 1462 ◽  
Author(s):  
Marinko V. Sarunic ◽  
Seth Weinberg ◽  
Joseph A. Izatt
Keyword(s):  
Swept Source ◽  
Full Field ◽  
Phase Microscopy ◽  
Source Phase

Swept source digital holographic phase microscopy

2016 ◽  
Vol 41 (4) ◽  
pp. 665 ◽  
Author(s):  
Shichao Chen ◽  
Junghyun Ryu ◽  
Kiho Lee ◽  
Yizheng Zhu
Keyword(s):  
Swept Source ◽  
Phase Microscopy

Performance and applications of the holography electron microscope

1993 ◽  
Vol 51 ◽  
pp. 1078-1079
Author(s):  
Akira Tonomura
Keyword(s):  
Electron Beam ◽  
Electron Microscope ◽  
Phase Measurement ◽  
Electron Holography ◽  
Imaging Method ◽  
High Contrast ◽  
Magnetic Lens ◽  
High Brightness ◽  
Holographic Imaging ◽  
Dynamic Observation

Electron holography is a two-step imaging method. However, the ultimate performance of holographic imaging is mainly determined by the brightness of the electron beam used in the hologram-formation process. In our 350kV holography electron microscope (see Fig. 1), the decrease in the inherently high brightness of field-emitted electrons is minimized by superposing a magnetic lens in the gun, for a resulting value of 2 × 109 A/cm2 sr. This high brightness has lead to the following distinguished features. The minimum spacing (d) of carrier fringes is d = 0.09 Å, thus allowing a reconstructed image with a resolution, at least in principle, as high as 3d=0.3 Å. The precision in phase measurement can be as high as 2π/100, since the position of fringes can be known precisely from a high-contrast hologram formed under highly collimated illumination. Dynamic observation becomes possible because the current density is high.

Electron interference and phase microscopy

1961 ◽  
Vol 74 (7) ◽  
pp. 553-566
Author(s):  
V.I. Milyutin
Keyword(s):  
Phase Microscopy ◽  
Electron Interference

Characterization of Ischemic Stroke in CT Images using Image Processing

2017 ◽  
Vol 7 (9) ◽  
pp. 18
Author(s):  
Amal Alzain ◽  
Suhaib Alameen ◽  
Rani Elmaki ◽  
Mohamed E. M. Gar-Elnabi
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Classification Accuracy ◽  
Ct Images ◽  
Gray Level ◽  
Level Variation ◽  
Interactive Data ◽  
The Brain ◽  
Brain Tissues

This study concern to characterize the brain tissues to ischemic stroke, gray matter, white matter and CSF using texture analysisto extract classification features from CT images. The First Order Statistic techniques included sevenfeatures. To find the gray level variation in CT images it complements the FOS features extracted from CT images withgray level in pixels and estimate the variation of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level of images. The results show that the Gray Level variation and   features give classification accuracy of ischemic stroke 97.6%, gray matter95.2%, white matter 97.3% and the CSF classification accuracy 98.0%. The overall classification accuracy of brain tissues 97.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate brain tissues names.

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