Integrating prior information into microwave tomography Part 1: Impact of detail on image quality

2017 ◽  
Vol 44 (12) ◽  
pp. 6461-6481 ◽  
Author(s):  
Douglas Kurrant ◽  
Anastasia Baran ◽  
Joe LoVetri ◽  
Elise Fear
Keyword(s):  
Image Quality ◽  
Prior Information ◽  
Microwave Tomography

Integrating prior information into microwave tomography part 2: Impact of errors in prior information on microwave tomography image quality

2017 ◽  
Vol 44 (12) ◽  
pp. 6482-6503 ◽  
Author(s):  
Douglas Kurrant ◽  
Elise Fear ◽  
Anastasia Baran ◽  
Joe LoVetri
Keyword(s):  
Image Quality ◽  
Prior Information ◽  
Microwave Tomography ◽  
Tomography Image

scholarly journals Study of Microwave Tomography Measurement Setup Configurations for Breast Cancer Detection Based on Breast Compression

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Alvaro Diaz-Bolado ◽  
Paul-Andre Barriere ◽  
Jean-Jacques Laurin
Keyword(s):  
Breast Cancer ◽  
Image Quality ◽  
Cancer Detection ◽  
Synthetic Data ◽  
Singular Value ◽  
Breast Cancer Detection ◽  
Single Frequency ◽  
Microwave Tomography ◽  
Breast Compression ◽  
Value Decomposition

Microwave tomography (MT) measurement setups for different configurations based on breast compression are compared to classical circular measurement setups. Configurations based on compression allow measuring the evanescent component of the scattered field and lead to a compact measurement setup that allows direct image comparison with a standard mammography system. The different configurations are compared based on the singular value decomposition (SVD) of the radiation operator for a 2D TM case. This analysis allows determining under which conditions the image quality obtained from the reconstructions can be enhanced. These findings are confirmed by a series of reconstructions of breast phantoms based on synthetic data obtained at a single frequency of operation.

Estimation and Use of Prior Information in FEM-CSI for Biomedical Microwave Tomography

2012 ◽  
Vol 11 ◽  
pp. 1606-1609 ◽  
Author(s):  
Amer Zakaria ◽  
Anastasia Baran ◽  
Joe LoVetri
Keyword(s):  
Prior Information ◽  
Microwave Tomography

Improvement of X-ray CT image quality by use of prior information

1999 ◽  
Vol 30 (11) ◽  
pp. 67-76
Author(s):  
Masami Tomizawa ◽  
Yoshinori Taniwaki ◽  
Shigeo Mikoshiba ◽  
Shin Hasegawa
Keyword(s):  
Image Quality ◽  
Prior Information ◽  
Ct Image ◽  
X Ray ◽  
Ct Image Quality

scholarly journals AN IMPROVED AERIAL REMOTE SENSING IMAGE DEFOGGING METHOD BASED ON DARK CHANNEL PRIOR INFORMATION

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1025-1030
Author(s):  
Z. Zhang ◽  
W. Feng ◽  
T. Wang ◽  
Y. Zhang ◽  
L. Ding
Keyword(s):  
Remote Sensing ◽  
Image Quality ◽  
Prior Information ◽  
Remote Sensing Image ◽  
Dark Channel Prior ◽  
Visual Effect ◽  
Image Defogging ◽  
Dark Channel ◽  
Aerial Remote Sensing ◽  
Color Cast

Aerial remote sensing image is widely used due to its high resolution, abundant information and convenient processing. However, its image quality is easily influenced by clouds and fog. In recent years, fog and haze air pollution is becoming more and more serious in the north of China and its influence on aerial remote sensing image quality is especially obvious. Considering the characters that aerial remote image is usually in huge amount of data and seldom covers sky area, this paper proposes an improved aerial remote sensing image defogging method based on dark channel prior information. First, a 2 % linear stretching is applied to eliminate the haze offset effect and provide a better initial value for later defogging processing. Then the dark channel prior image is obtained by calculating the minimum values of r, g, b channels of each pixel directly. Subsequently, according to the particularity of aerial image, the adaptive threshold t0 is set up to improve the defogging effect. Finally, to improve the color cast phenomenon, a way called automatic color method is introduced to enhance the visual effect of defogged image. Experiments are performed on normal image in fog and on aerial remote sensing image in fog. Experimental results prove that the proposed method can obtain the defogged image with better visual effect and image quality. Moreover, the improved method significantly balances the color information in the defogged image and efficiently avoids the color cast phenomenon.

scholarly journals Microwave Imaging of Human Forearms: Pilot Study and Image Enhancement

2013 ◽  
Vol 2013 ◽  
pp. 1-17 ◽  
Author(s):  
Colin Gilmore ◽  
Amer Zakaria ◽  
Stephen Pistorius ◽  
Joe LoVetri
Keyword(s):  
Adipose Tissue ◽  
Pilot Study ◽  
Image Quality ◽  
Prior Information ◽  
Microwave Imaging ◽  
Scattering Data ◽  
Source Inversion ◽  
Inversion Algorithm ◽  
Microwave Scattering ◽  
Imaging Results

We present a pilot study using a microwave tomography system in which we image the forearms of 5 adult male and female volunteers between the ages of 30 and 48. Microwave scattering data were collected at 0.8 to 1.2 GHz with 24 transmitting and receiving antennas located in a matching fluid of deionized water and table salt. Inversion of the microwave data was performed with a balanced version of the multiplicative-regularized contrast source inversion algorithm formulated using the finite-element method (FEM-CSI). T1-weighted MRI images of each volunteer’s forearm were also collected in the same plane as the microwave scattering experiment. Initial “blind” imaging results from the utilized inversion algorithm show that the image quality is dependent on the thickness of the arm’s peripheral adipose tissue layer; thicker layers of adipose tissue lead to poorer overall image quality. Due to the exible nature of the FEM-CSI algorithm used, prior information can be readily incorporated into the microwave imaging inversion process. We show that by introducing prior information into the FEM-CSI algorithm the internal anatomical features of all the arms are resolved, significantly improving the images. The prior information was estimated manually from the blind inversions using anad hocprocedure.

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