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Markov random field aided Bayesian approach for image reconstruction in confocal microscopy
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10.1063/1.2770961
/content/aip/journal/jap/102/4/10.1063/1.2770961
http://aip.metastore.ingenta.com/content/aip/journal/jap/102/4/10.1063/1.2770961

Figures

Image of FIG. 1.
FIG. 1.

The directional derivatives along direction in a neighborhood centered at in the plane of a 3D object.

Image of FIG. 2.
FIG. 2.

Csiszár I-divergence vs iteration plot for ML, MAP-Quad, and MAP-FL algorithms.

Image of FIG. 3.
FIG. 3.

I-divergence vs hyperparameter plot for MAP-based algorithms.

Image of FIG. 4.
FIG. 4.

(a) Original raw 3D microscopy image. 3D reconstructed images (pseudo olor) using, (b) ML, (c) MAP-Quad, and (d) MAP-FL algorithms.

Image of FIG. 5.
FIG. 5.

Slice view (slice No. 34) of the (a) original, (b) distorted object and reconstructed object using (c) ML, (d) MAP-Quad, (e) MAP-FL algorithms.

Image of FIG. 6.
FIG. 6.

(a), (e), and (i) are, respectively, the raw microscopic images. The associated two images are the optical slice from two different axial views along the line (right image) and (bottom image). [(b), (f), (j)], [(c), (g), (k)], and [(d), (h), (l)} are the corresponding ML-, MAP-Quad-, and MAP-FL-reconstructed images.

Image of FIG. 7.
FIG. 7.

(a) and (e) are the raw microscopic data at NA 0.6 and 1.4, respectively. [(b), (c), (d)] and [(f), (g), (h)] are the reconstructed images using ML, MAP-Quad, MAP-FL algorithms at numerical aperture 0.6 and 1.4, respectively.

Image of FIG. 8.
FIG. 8.

Line plots along different regions of simulated phantom and real object.

Image of FIG. 9.
FIG. 9.

(a) Original phantom, [(b), (f), (j)] are images that are Gaussian blurred and Poisson noised with version of original phantom. [(c), (d), (e)] are ML-, MAP-Quad-, and MAP-FL-reconstructed images at . Similarly, [(g), (h), (i)] and [(k), (l), (m)] are ML-, MAP-Quad-, and MAP-FL-reconstructed images at and 35, respectively.

Tables

Generic image for table
Table I.

Description of stopping criterion for ML, MAP-Quad, and MAP-FL algorithms at a threshold of .

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/content/aip/journal/jap/102/4/10.1063/1.2770961
2007-08-22
2014-04-21
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Markov random field aided Bayesian approach for image reconstruction in confocal microscopy
http://aip.metastore.ingenta.com/content/aip/journal/jap/102/4/10.1063/1.2770961
10.1063/1.2770961
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