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Algorithmic methods in diffraction m...
~
Thibault, Pierre.
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Algorithmic methods in diffraction microscopy.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Algorithmic methods in diffraction microscopy./
作者:
Thibault, Pierre.
面頁冊數:
232 p.
附註:
Adviser: Veit Elser.
Contained By:
Dissertation Abstracts International69-01B.
標題:
Physics, Optics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3292777
ISBN:
9780549412168
Algorithmic methods in diffraction microscopy.
Thibault, Pierre.
Algorithmic methods in diffraction microscopy.
- 232 p.
Adviser: Veit Elser.
Thesis (Ph.D.)--Cornell University, 2007.
The main topic of this thesis is the development of algorithmic techniques in diffraction microscopy. In addition to introducing new methods, it is meant to be a review of the algorithmic aspects of the field of diffractive imaging.
ISBN: 9780549412168Subjects--Topical Terms:
1018756
Physics, Optics.
Algorithmic methods in diffraction microscopy.
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The main topic of this thesis is the development of algorithmic techniques in diffraction microscopy. In addition to introducing new methods, it is meant to be a review of the algorithmic aspects of the field of diffractive imaging.
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Recent diffraction imaging techniques use properties of coherent sources (most notably x-rays and electrons) to transfer a portion of the imaging task to computer algorithms. "Diffraction microscopy" is a method which consists in reconstructing the image of a specimen from its diffraction pattern. Because only the amplitude of a wavefield incident on a detector is measured, reconstruction of the image entails to recovering the lost phases. This extension of the 'phase problem" commonly met in crystallography is solved only if additional information is available.
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An overview of the scattering approximations used in the interpretation of diffraction datasets is first given, as well as a numerical propagation tool useful in conditions where known approximations fail. Concepts central to diffraction microscopy---such as oversampling---are then introduced and other similar imaging techniques described.
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A complete description of iterative reconstruction algorithms follows, with a special emphasis on the difference map, the algorithm used in this thesis. The formalism, based on constraint sets and projection onto these sets, is then defined and explained. Simple projections commonly used in diffraction imaging are then described.
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The various ways experimental realities can affect reconstruction methods will then be enumerated. Among the diverse sources of algorithmic difficulties, one finds that noise, missing data and partial coherence are typically the most important. Other related difficulties discussed are the detrimental effects of crystalline domains in a specimen, and the convergence problems occurring when the support of a complex-valued specimen is not well known.
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The last part of this thesis presents reconstruction results; an account is given on real specimen reconstruction from x-ray data (a yeast cell, and a quasicrystal electron density) and from visible light experiments (insect wings). Simulated data in various multiple-measurements experiments are also reconstructed using a new iterative approach.
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