Image reconstruction from a limited number of projections: Detection/estimation of multiple discs with unknown radii

Song Wang; Bede Liu; Sanjeev Kulkarni

doi:10.1109/ICIP.1994.413476

Image reconstruction from a limited number of projections: Detection/estimation of multiple discs with unknown radii

Song Wang, Bede Liu, Sanjeev Kulkarni

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

Considers the problem of tomographic image reconstruction from a limited number of noisy projections. Maximum likelihood estimation is used to reconstruct an image of multiple discs with unknown locations and radii. An efficient algorithm is developed to tackle the computation. The algorithm is successfully applied to images containing as many as twelve discs with widely varying radii and with signal-to-noise ratio as low as 0 dB, and the number of projections used is as few as 16. Experimental results show that the approach significantly outperforms the conventional convolution back-projection method.

Original language	English (US)
Article number	413476
Pages (from-to)	854-858
Number of pages	5
Journal	Proceedings - International Conference on Image Processing, ICIP
Volume	2
DOIs	https://doi.org/10.1109/ICIP.1994.413476
State	Published - 1994
Event	The 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA Duration: Nov 13 1994 → Nov 16 1994

All Science Journal Classification (ASJC) codes

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.1994.413476

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title = "Image reconstruction from a limited number of projections: Detection/estimation of multiple discs with unknown radii",

abstract = "Considers the problem of tomographic image reconstruction from a limited number of noisy projections. Maximum likelihood estimation is used to reconstruct an image of multiple discs with unknown locations and radii. An efficient algorithm is developed to tackle the computation. The algorithm is successfully applied to images containing as many as twelve discs with widely varying radii and with signal-to-noise ratio as low as 0 dB, and the number of projections used is as few as 16. Experimental results show that the approach significantly outperforms the conventional convolution back-projection method.",

author = "Song Wang and Bede Liu and Sanjeev Kulkarni",

note = "Publisher Copyright: {\textcopyright} 1994 IEEE.; The 1994 1st IEEE International Conference on Image Processing ; Conference date: 13-11-1994 Through 16-11-1994",

year = "1994",

doi = "10.1109/ICIP.1994.413476",

language = "English (US)",

volume = "2",

pages = "854--858",

journal = "Proceedings - International Conference on Image Processing, ICIP",

issn = "1522-4880",

publisher = "IEEE Computer Society",

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T1 - Image reconstruction from a limited number of projections

T2 - The 1994 1st IEEE International Conference on Image Processing

AU - Wang, Song

AU - Liu, Bede

AU - Kulkarni, Sanjeev

PY - 1994

Y1 - 1994

N2 - Considers the problem of tomographic image reconstruction from a limited number of noisy projections. Maximum likelihood estimation is used to reconstruct an image of multiple discs with unknown locations and radii. An efficient algorithm is developed to tackle the computation. The algorithm is successfully applied to images containing as many as twelve discs with widely varying radii and with signal-to-noise ratio as low as 0 dB, and the number of projections used is as few as 16. Experimental results show that the approach significantly outperforms the conventional convolution back-projection method.

AB - Considers the problem of tomographic image reconstruction from a limited number of noisy projections. Maximum likelihood estimation is used to reconstruct an image of multiple discs with unknown locations and radii. An efficient algorithm is developed to tackle the computation. The algorithm is successfully applied to images containing as many as twelve discs with widely varying radii and with signal-to-noise ratio as low as 0 dB, and the number of projections used is as few as 16. Experimental results show that the approach significantly outperforms the conventional convolution back-projection method.

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DO - 10.1109/ICIP.1994.413476

M3 - Conference article

AN - SCOPUS:84997541888

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SP - 854

EP - 858

JO - Proceedings - International Conference on Image Processing, ICIP

JF - Proceedings - International Conference on Image Processing, ICIP

M1 - 413476

Y2 - 13 November 1994 through 16 November 1994

ER -

Image reconstruction from a limited number of projections: Detection/estimation of multiple discs with unknown radii

Abstract

All Science Journal Classification (ASJC) codes

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