Published August 7, 2009 | Version v1
Journal article

Deconvolution of x-ray phase contrast images as a way to retrieve phase information lost due to insufficient resolution

  • 1. Department of Medical Physics and Bioengineering, UCL, London WC1E 6BT (United Kingdom)

Description

When free-space propagation x-ray phase contrast imaging is implemented outside synchrotron radiation facilities, the combined effect of detector resolution and source size swamps the fine phase contrast fringes, often making them almost undetectable. In an attempt to mitigate this effect, a simple deconvolution procedure based on division in the Fourier space plus multiplication by an appropriate filter was applied to experimental x-ray phase contrast images of a simple geometric phantom. The filter parameter was varied in order to assess its impact on the level of retrieved phase signal. The deconvolved images were compared to simulated ones obtained under different resolution conditions, showing that this simple procedure provided signals equivalent to those that would be obtained with a detector with three times better resolution. By accepting an increase in the overall image noise, the method also appears to bring up secondary phase contrast fringes, which are not visible in the unprocessed signal. (note)

Availability note (English)

Available from http://dx.doi.org/10.1088/0031-9155/54/15/N02

Additional details

Identifiers

DOI
10.1088/0031-9155/54/15/N02;
PII
S0031-9155(09)16254-1;

Publishing Information

Journal Title
Physics in Medicine and Biology
Journal Volume
54
Journal Issue
15
Journal Page Range
p. N347-N354
ISSN
0031-9155
CODEN
PHMBA7

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
41050855
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
IMAGES; NOISE; PHANTOMS; RADIATION DETECTORS; RESOLUTION; SIMULATION; X RADIATION
Descriptors DEC
ELECTROMAGNETIC RADIATION; IONIZING RADIATIONS; MEASURING INSTRUMENTS; MOCKUP; RADIATIONS; STRUCTURAL MODELS