M. V. OLIVA, H. H. MUHAMMED
between the original model and the reconstructed one,
but the difference in terms of a calculated PSNR value of
21 dB is quite considerable. But this doesn’t mean that
the method doesn’t work properly. It reflects that new
details appear in the reconstructed volume which could
be closer to the real 3D model without missing data .
5. Discussion and Conclusions
The purpose of our work was to apply a new method to
solve LPAs (e.g. with a missing cone or a missing wedge
of the acquired image-data volume) in TEM data. The
method was applied to different d atasets and the resu lting
reconstructed image volumes were evaluated. Good 3D
reconstruction results were obtained. The PSNR values
were calculated for all resulting reconstructed images.
These PSNR values were better than those obtained us-
ing existing commonly used techniques, such as POCS.
The approa ch proposed in our work can be cons idered as
a great breakthrough, because for data acquisitions li-
mited to [45˚, −45˚], POCS results in an error-rate ar ound
40%, while our approach achieves an error-rate lower
than 1% for the Hansandrey and the viral DNA gatekee-
per cases when 50% of the acquired data is missing.
However, different acquisition technique and proce-
dures will produce data with different sparsity characte-
ristics in frequency domain, which in its turn will affect
the performance of our method. For example, if a large
portion of the high frequency zones of the acquired data
is missing or corrupted, then it gets much more difficult
to reconstruct the missing part of the 3D model because
the algorithm doesn’t have e n ough prior information.
Therefore, we have to take under consideration that a
test measure is needed to determine which datasets, with
the presence of missing data, are valid or not to apply the
proposed method and get good 3D reconstruction resu lts.
If such a test is performed, it will be possible to know if
the obtained 3D reconstruction result is supposed to be
similar to the real original model (i.e. without missing
data) or not. Then it will be possible to know if the 3D
reconstruction of Philip’s crystallography dataset (pre-
sented in Figure 6) is correct or not.
One of the most exciting research projects that could
emerge from our work is the possibility to develop a new
optimized acquisition technique or procedure for TEM.
In addition, achieving a considerable reduction of radia-
tion dose applied to the specimen. Another possibility is
to adapt the proposed method and apply it to other kinds
of modalities like Computed Tomography (CT), Mag-
netic Resonance Imaging (MRI), astronomy, geophysical
exploration or other type of electron microscope tech-
niques. Since a complete reconstruction of the Hansand-
rey model took 32 hours in a common laptop (4-core 2.0
GHz and 4 Gb RAM), it would be necessary to speed up
the algorithm by implementing it using GPU techniques
(e.g. CUDA, OpenCL).
6. Acknowledgements
This paper would not have been possible without the
support and help of Dr. Philip Koeck (from the Royal
Institute of Technolog y KTH, Sweden) who supplied th e
Hansandrey dataset and Philip’s crystallography dataset.
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