Analysis of spatial-temporal regularization methods for linear inverse problems from a common statistical framework
In some medical imaging problems, the quantity to image is time-varying but related to the measurements by spatial dynamics only. Traditional methods solve the associated inverse problem separately at each time instant. Several recent reports take advantage of prior knowledge and/or measurement temp...
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| creator | Yiheng Zhang Ghodrati, A. Brooks, D.H. |
| description | In some medical imaging problems, the quantity to image is time-varying but related to the measurements by spatial dynamics only. Traditional methods solve the associated inverse problem separately at each time instant. Several recent reports take advantage of prior knowledge and/or measurement temporal behavior to solve jointly in space and time. In this paper we discuss three such approaches, which have been introduced in distinct mathematical contexts, from a common statistical regularization framework, and illuminate their relationships, advantages and disadvantages. |
| doi_str_mv | 10.1109/ISBI.2004.1398652 |
| format | Conference Proceeding |
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Traditional methods solve the associated inverse problem separately at each time instant. Several recent reports take advantage of prior knowledge and/or measurement temporal behavior to solve jointly in space and time. 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Traditional methods solve the associated inverse problem separately at each time instant. Several recent reports take advantage of prior knowledge and/or measurement temporal behavior to solve jointly in space and time. In this paper we discuss three such approaches, which have been introduced in distinct mathematical contexts, from a common statistical regularization framework, and illuminate their relationships, advantages and disadvantages.</abstract><pub>IEEE</pub><doi>10.1109/ISBI.2004.1398652</doi></addata></record> |
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| identifier | ISBN: 0780383885 |
| ispartof | 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821), 2004, p.772-775 Vol. 1 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biomedical imaging Biomedical measurements Covariance matrix Extraterrestrial measurements Image reconstruction Inverse problems Kalman filters Noise measurement Systems engineering and theory Time measurement |
| title | Analysis of spatial-temporal regularization methods for linear inverse problems from a common statistical framework |
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