Sinogram enhancement for tomographic sensing systems with limited resources

Eugenio P A Constantino; Krikor B. Ozanyan

doi:10.1109/ICSENS.2007.355518

Sinogram enhancement for tomographic sensing systems with limited resources

Eugenio P A Constantino, Krikor B. Ozanyan

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

Abstract

In this work we propose a novel method to address imaging with incomplete data from Tomography imaging sensors by utilizing techniques from the area of image processing. To achieve this, the problem of incomplete projection data is formulated as a sinogram recovery problem. The method is introduced and demonstrated in the case of noisy signals in limited-angle and sparse-angle tomography. The full measurement space (the sinogram) is treated as an image, pixellated according to the attainable spatial resolution, which allows the application of algorithms developed for image processing. Hough transform (HT) is used to estimate the missing projections by identifying the major sinusoidal patterns corresponding to higher intensity clusters in the object space. This method bypasses the traditional cumbersome interpolation techniques and the laborious computation of long iterations in solving the inverse problem. © 2006 IEEE.

Original language	English
Title of host publication	Proceedings of IEEE Sensors\|Proc. IEEE Sens.
Pages	514-517
Number of pages	3
DOIs	https://doi.org/10.1109/ICSENS.2007.355518
Publication status	Published - 2006
Event	2006 5th IEEE Conference on Sensors - Daegu Duration: 1 Jul 2006 → …

Conference

Conference	2006 5th IEEE Conference on Sensors
City	Daegu
Period	1/07/06 → …

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10.1109/ICSENS.2007.355518

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@inproceedings{1a635faefce24965ae096f94ff3aa711,

title = "Sinogram enhancement for tomographic sensing systems with limited resources",

abstract = "In this work we propose a novel method to address imaging with incomplete data from Tomography imaging sensors by utilizing techniques from the area of image processing. To achieve this, the problem of incomplete projection data is formulated as a sinogram recovery problem. The method is introduced and demonstrated in the case of noisy signals in limited-angle and sparse-angle tomography. The full measurement space (the sinogram) is treated as an image, pixellated according to the attainable spatial resolution, which allows the application of algorithms developed for image processing. Hough transform (HT) is used to estimate the missing projections by identifying the major sinusoidal patterns corresponding to higher intensity clusters in the object space. This method bypasses the traditional cumbersome interpolation techniques and the laborious computation of long iterations in solving the inverse problem. {\textcopyright} 2006 IEEE.",

author = "Constantino, {Eugenio P A} and Ozanyan, {Krikor B.}",

year = "2006",

doi = "10.1109/ICSENS.2007.355518",

language = "English",

isbn = "1424403766",

pages = "514--517",

booktitle = "Proceedings of IEEE Sensors|Proc. IEEE Sens.",

note = "2006 5th IEEE Conference on Sensors ; Conference date: 01-07-2006",

}

TY - GEN

T1 - Sinogram enhancement for tomographic sensing systems with limited resources

AU - Constantino, Eugenio P A

AU - Ozanyan, Krikor B.

PY - 2006

Y1 - 2006

N2 - In this work we propose a novel method to address imaging with incomplete data from Tomography imaging sensors by utilizing techniques from the area of image processing. To achieve this, the problem of incomplete projection data is formulated as a sinogram recovery problem. The method is introduced and demonstrated in the case of noisy signals in limited-angle and sparse-angle tomography. The full measurement space (the sinogram) is treated as an image, pixellated according to the attainable spatial resolution, which allows the application of algorithms developed for image processing. Hough transform (HT) is used to estimate the missing projections by identifying the major sinusoidal patterns corresponding to higher intensity clusters in the object space. This method bypasses the traditional cumbersome interpolation techniques and the laborious computation of long iterations in solving the inverse problem. © 2006 IEEE.

AB - In this work we propose a novel method to address imaging with incomplete data from Tomography imaging sensors by utilizing techniques from the area of image processing. To achieve this, the problem of incomplete projection data is formulated as a sinogram recovery problem. The method is introduced and demonstrated in the case of noisy signals in limited-angle and sparse-angle tomography. The full measurement space (the sinogram) is treated as an image, pixellated according to the attainable spatial resolution, which allows the application of algorithms developed for image processing. Hough transform (HT) is used to estimate the missing projections by identifying the major sinusoidal patterns corresponding to higher intensity clusters in the object space. This method bypasses the traditional cumbersome interpolation techniques and the laborious computation of long iterations in solving the inverse problem. © 2006 IEEE.

U2 - 10.1109/ICSENS.2007.355518

DO - 10.1109/ICSENS.2007.355518

M3 - Conference contribution

SN - 1424403766

SN - 9781424403769

SP - 514

EP - 517

BT - Proceedings of IEEE Sensors|Proc. IEEE Sens.

T2 - 2006 5th IEEE Conference on Sensors

Y2 - 1 July 2006

ER -

Sinogram enhancement for tomographic sensing systems with limited resources

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