OSA's Digital Library

Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 21, Iss. 21 — Oct. 21, 2013
  • pp: 25389–25402
« Show journal navigation

THz phase-contrast computed tomography based on Mach-Zehnder interferometer using continuous wave source: proof of the concept

Masayuki Suga, Yoshiaki Sasaki, Takeshi Sasahara, Tetsuya Yuasa, and Chiko Otani  »View Author Affiliations


Optics Express, Vol. 21, Issue 21, pp. 25389-25402 (2013)
http://dx.doi.org/10.1364/OE.21.025389


View Full Text Article

Acrobat PDF (4633 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

In this study, we propose a THz computed tomography (CT) method based on phase contrast, which retrieves the phase shift information at each data point through a phase modulation technique using a Mach-Zehnder interferometer with a continuous wave (CW) source. The THz CT is based on first-generation CT, which acquires a set of projections by translational and rotational scans using a thin beam. From the phase-shift projections, we reconstruct a spatial distribution of refractive indices in a cross section of interest. We constructed a preliminary system using a highly coherent CW THz source with a frequency of 0.54 THz to prove the concept and performed an imaging experiment using phantoms to investigate its imaging features such as artifact-immune imaging, quantitative measurement, and selective detection.

© 2013 Optical Society of America

1. Introduction

The terahertz (THz) wave is an electromagnetic wave with a frequency that lies between radio and infrared frequencies, ranging from 0.1 to 10 THz, corresponding to a wavelength of 3 mm to 30 μm. The recent developments in THz optical devices have accelerated the research on THz imaging [1

1. B. B. Hu and M. C. Nuss, “Imaging with terahertz waves,” Opt. Lett. 20(16), 1716–1718 (1995). [CrossRef] [PubMed]

8

8. Y. Kawada, T. Yasuda, H. Takahashi, and S. Aoshima, “Real-time measurement of temporal waveforms of a terahertz pulse using a probe pulse with a tilted pulse front,” Opt. Lett. 33(2), 180–182 (2008). [CrossRef] [PubMed]

]. A variety of imaging methods have been proposed to take advantage of the characteristics of THz waves. For instance, transillumination imaging, which is similar to X-ray imaging, can be realized based on the high transmissivity of THz waves for certain materials such as paper, wood, powder, semiconductors, and plastic. Consequently, this imaging can also be extended to the tomographic mode, analogous to X-ray computed tomography (CT) [9

9. C. Kak and M. Slanery, “Principles of Computerized Tomographic Imaging,” New York: IEEE Press (1987).

]. Early THz tomographic imaging was based on the measurement of the time-of-flight of the reflected pulses [10

10. D. M. Mittleman, S. Hunsche, L. Boivin, and M. C. Nuss, “T-ray tomography,” Opt. Lett. 22(12), 904–906 (1997). [CrossRef] [PubMed]

]. This technique reproduces the 3D refractive index profiles of objects consisting of well-separated layers of different refractive indices, which provides an extremely high depth resolution on the order of 1 μm. Subsequently, a multi-color THz-CT system using time-domain spectroscopy was developed [11

11. B. Ferguson, S. Wang, D. Gray, D. Abbot, and X. C. Zhang, “T-ray computed tomography,” Opt. Lett. 27(15), 1312–1314 (2002). [CrossRef] [PubMed]

13

13. E. Abraham, A. Younus, C. Aguerre, P. Desbarats, and P. Mounaix, “Refraction losses in terahertz computed tomography,” Opt. Commun. 283(10), 2050–2055 (2010). [CrossRef]

]. In the experiments leading to this development, the tomographic information was reproduced based on the same CT reconstruction algorithm as that used in X-ray CT. This imaging system simultaneously forms cross-sectional images by absorption and phase contrasts in a sample with a complicated structure and a spatial resolution on the order of sub millimeters.

On the other hand, from the viewpoint of CT imaging, the effects of reflection and refraction are substantial as compared to X-rays when the sample is bulky, because the refractive indices in THz regions are relatively large. Therefore, the mismatch in refractive indices causes unintended intensity dissipation in the incident direction, owing to refraction, reflection, and scattering, especially at the boundaries between air and material. As the unintended intensity dissipation is apparently regarded as attenuation at the boundary, the adoption of an imaging protocol similar to that of X-ray CT based on attenuation contrast results in the appearance of remarkable artifacts in the reconstructed image at the boundary, leading to impaired quantitative observations [17

17. N. Sunaguchi, Y. Sasaki, N. Maikusa, M. Kawai, T. Yuasa, and C. Otani, “Depth-resolving THz imaging with tomosynthesis,” Opt. Express 17(12), 9558–9570 (2009). [CrossRef] [PubMed]

]. In contrast, the phase-shift is not influenced by the intensity dissipation at the boundary, and hence, artifact-free reconstruction is expected as long as the transmitted wave can be detected.

In this study, we propose a THz-CT method based on phase contrast with significantly reduced artifacts using a highly coherent CW source and a semiconductor detector. The THz-CT is based on first-generation CT, which acquires a set of projections by translational and rotational scans with the use of a thin beam [18

18. J. Hsieh, Computed Tomography Principles, Design, Artifacts, and Recent Advances, Second Edition (John Wiley & Sons, Inc. & SPIE, 2009).

]. At each data-point, the phase-shift is retrieved through a phase modulation technique using a Mach-Zehnder interferometer with a CW source. From the projections of the phase-shift, we reconstruct a spatial distribution of refractive indices in a cross section of interest. We constructed a preliminarily system to prove the concept and performed an imaging experiment using a polystyrene foam phantom to demonstrate the effectiveness of the proposed method.

2. Phase shift retrieval

Figure 1
Fig. 1 Conceptual diagram of phase-contrast THz-CT system based on the Mach–Zehnder interferometer.
shows a conceptual diagram of the proposed imaging system. In order to retrieve the phase shift from the transmitted intensity obtained from a single detector, we used a Mach-Zehnder interferometer. The thin parallel THz beam with high coherence from a CW source is split into the signal and local oscillator beams by the beam splitter BS1. The signal beam impinges on a sample, which is mounted on positioning devices so as to enable translation and rotation, and it is subjected to a variety of optical phenomena, such as refraction, reflection, scattering, and absorption, governed by inhomogeneous distribution of refractive indices in the sample. The transmitted beam retaining the propagation direction is mixed with the local oscillator beam, whose path length is adjusted using the reference mirror, at the beam splitter BS3. The mixed beam is detected by the SBD detector.

On the other hand, with the assumption that the refractive index n is unity in air, n – 1 is zero in the region outside the sample. Thus, from Eq. (8),
(n1)dz=0t(n1)dz=ϕ.
(17)
This means that the estimated phase shift is equal to the line integral of n – 1 along the direction of the signal beam propagation, that is, the projection data of n – 1. Therefore, by conducting the measurements while translating and rotating the sample according to the data-acquisition scheme in first-generation CT, we can prepare a set of projections. Using the filtered back projection (FBP) method, we can reconstruct the cross-section from the projections. Finally, noting that the reconstructed image is a spatial distribution of n – 1, we can easily determine the refractive-index distribution from the reconstructed image.

On the other hand, from Eq. (4), we find the value to be proportional to exp(0tμdz). Similar to the above calculation, assuming that the absorption term κ is zero in the region outside the sample, we obtain
μdz=0tμdz.
(18)
This is the line integral of the absorption coefficient. Therefore, we can simultaneously obtain the projections of the absorption coefficient from the measured data as well. However, we cannot obtain a high-quality reconstructed image, since the absorption projections are contaminated with unintended reflection, refraction, and scattering at the boundaries with the mismatch of the refractive index.

3. Experimental setup

Figure 2
Fig. 2 Schematic diagram of a preliminary phase-contrast THz-CT system.
shows a schematic of the THz-CT imaging system based on the Mach-Zehnder interferometer. A frequency-multiplier CW source with a frequency of 540 GHz and a wavelength of 555 µm (0.7 mW, Virginia Diodes, Inc.) is used as the light source. The amplitude of the THz wave from the source is modulated at 30 kHz with a rectangular waveform generated by a function generator for lock-in detection. The beam splitters (a), (b), and (c), shown in Fig. 2, are made from high-resistivity silicon wafer. The THz wave is collimated to a thin parallel beam with convex lenses and parabolic mirrors. The beam size of the signal beam before convex lens (b) and the reference beam are 6 mm in diameter. Here, we need multiple mirrors and lenses for producing a thin parallel beam because the output wave from the source is divergent, leading to reduced incident intensity in front of a sample.

The beam after interference is detected by the SBD detector (WR-1.2, Virginia Diodes, Inc.). The detected signal was fed into a preamplifier (with a gain of 5000), then into a lock-in amplifier (time constant 30 ms), and finally to a personal computer through a data acquisition card. The dynamic range of this system is 65 dB.

The CT data-acquisition protocol is based on first-generation CT. Translating a sample from one edge to the other edge of the sample using a translational positioning device at a predefined step yields a single projection data at a projection angle. Then, the projection data acquisition procedure is repeated over 360° while rotating the sample using a rotational positioning device at a predefined angular step. The cross-sectional image is reconstructed from the set of projections using the filtered back projection (FBP) method [20

20. A. Rosenfeld and C. Kak, Digital Picture Processing, 2nd Ed., Vol. I (Academic Press, 1982).

]. From Eq. (17), it can be seen that the reconstructed image corresponds to a distribution of refractive indices in the sample, because the projection data is a line integral of n – 1.

In the first-generation CT, the spot size of the beam should be held constant in the measurement range because the quality of the projection images depends on the uniformity of the beam cross section. Accordingly, we evaluated the beam profile using the knife-edge method. Figures 3(a)
Fig. 3 (a) Beam profile and (b) relationship between the beam diameter and the position in the direction of beam propagation.
and 3(b) show the beam profiles across and along the beam, as a function of the knife position. In Fig. 3(a), the red dotted curve is that for measured data, and the blue solid curve is that for differential data obtained from the raw measured data. A beam diameter of less than 2.5 mm was realized in the 40 mm depth around the focus, where the focal length of the convex lens positioned just upstream of the object was 101.6 mm. The sample was measured within this region of the beam. Thus, the spatial resolution of the CT system is broadly 2.5 mm.

4. Imaging experiment

In order to validate the imaging characteristics of the system, we imaged a polystyrene foam sphere of 30 mm in diameter and having two channels of 5 mm in diameter. Figures 4(a)
Fig. 4 A photograph of polystyrene foam phantom (a) from bird-view, and (b) from top-view. (c) Schematic of cross section of the phantom at the level where the diameter is maximum.
and 4(b) show the bird-view and top-view photographs of the phantom, respectively. Figure 4(c) is a schematic of the cross-section of the phantom at the level where the diameter of the cross-section is maximum. The sample was fixed in the translational and rotational stages such that the channels were perpendicular to the incident beam. After a series of 0.1-mm-step translational scanning procedures were completed, the sample was rotated in steps of 1°. A series of data acquisition procedures were performed over 360°, resulting in 360 projection data. Then, we performed a series of measurements by moving the reference mirror by λ/8 using the translational stage. We finally obtained four sets of projection data in a similar manner.

The raw sinograms obtained for the difference in path lengths between the signal and local oscillator arms of 0, λ/4, λ/2, and 3λ/4 are shown in Figs. 5(a)
Fig. 5 Raw sinograms obtained at differences in path length between the signal and local oscillator arms of (a) 0, (b) λ/4, (c) λ/2, and (d) 3 λ/4.
5(d), respectively, where each image was 400 × 360 pixels in size. The brightness varies with the difference in path length. Figure 6(a)
Fig. 6 (a) Wrapped sinogram estimated using Eq. (13) from Figs. 5, and (b) line profile of the first row of Fig. 6(a).
shows the sinogram image of the phase-shift estimated by Eq. (13) from the four sets of raw sinogram images shown in Fig. 5. Figure 6(b) shows a line profile of the first row of the sinogram, which is indicated by a red line in Fig. 6(a). We observe that a jump of 2π occurs at the boundaries between air and the sample. This is owing to the fact that the phase-shift is wrapped between –π and π because of the arctangent in Eq. (13). Therefore, the wrapped sinogram presents discontinuities at the boundaries. It is necessary to unwrap the sinogram to obtain projections from which the cross-sectional images are reconstructed. We applied the phase-unwrap algorithm devised by Cusack et al [21

21. R. Cusack, J. M. Huntley, and H. T. Goldrein, “Improved noise-immune phase-unwrapping algorithm,” Appl. Opt. 34(5), 781–789 (1995). [CrossRef] [PubMed]

]. Figure 7(a)
Fig. 7 (a) Unwrapped sinogram estimated using Eq. (13) from Figs. 5, and (b) line profile of the first row of Fig. 7(a).
is an unwrapped sinogram obtained from Fig. 6(a), and Fig. 7(b) is a line profile of the first row of Fig. 7(a). Through this algorithm, the wrapped phase-shift is satisfactorily unwrapped. Next, we reconstructed the cross section from the sinogram using the FBP algorithm with a Shepp-Logan filter [20

20. A. Rosenfeld and C. Kak, Digital Picture Processing, 2nd Ed., Vol. I (Academic Press, 1982).

]. Figure 8(a)
Fig. 8 (a) THz-CT image based on phase-contrast, (b) THz-CT image based on attenuation-contrast, and (c) profiles along the red lines indicated in Figs. 8(a) and 8(b).
shows the phase-contrast THz-CT image of the phantom at the level, at which the cross-sectional diameter is maximum. For comparison, we reconstructed an absorption-contrast image (Fig. 8(b)) from the same four sets of the raw sinograms using Eq. (18). In both the reconstructed images, the pixel values were normalized in 8-bit gradation. Figure 8(c) compares the profiles of both these images along the red lines shown in Figs. 8(a) and 8(b), by plotting the pixel value as a function of the position. The blue and red curves in Fig. 8(c) correspond to the profiles of the phase- and attenuation-contrast CT images, respectively. In the attenuation-contrast CT, remarkable artifacts are observed at the boundary between air and polystyrene foam regions. In addition, the pixel value in some regions is much lower than that in the air region, although the pixel value in air is zero. These facts indicate that the attenuation-contrast CT can enable neither artifact-free reconstruction nor quantitative measurement. On the other hand, no remarkable artifacts are observed in the phase-contrast CT image.

As discussed in Section 2, pixel values in the reconstructed phase-contrast CT image represent the refractive indices. Using Eq. (17), we recalculated an average pixel value denoted by the yellow rectangle (120 × 60 pixels) indicated in Fig. 8(a). The estimated refractive index in polystyrene foam ranges from 1.02 to 1.035, and the average and standard deviation are 1.026 and 0.003, respectively. In reference [22

22. G. Zhao, M. Mors, T. Wenckebach, and P. C. M. Planken, “Terahertz dielectric properties of polystyrene foam,” J. Opt. Soc. Am. B 19(6), 1476–1479 (2002). [CrossRef]

], it was reported that the refractive index of polystyrene foam ranges from 1.016 to 1.022. The values are similar to our estimated average value.

Although the estimated refractive indices in air regions should be almost zero, those in the channel regions take finite values as shown in Fig. 8(c). This is because the diameter of the channels is relatively large as compared to the diameter of the beam cross section. If the beam diameter is sufficiently less than the channel diameter, the nonconformity is dissolved.

5. Selective detection from scattered wave

The proposed imaging system is based on the Mach-Zehnder interferometer. The reasons behind the use of the interferometer are the ability to measure phase-shift information using a CW source with a high coherence and the ability to selectively detect the forward-scattered directional component from multiply and divergently scattered waves emerging from the sample through the mixing of the signal beam with the local oscillator beam. The ability of selective detection of the forward-scattered waves was experimentally investigated using a sample to induce multiple scattering. Figures 9(a)
Fig. 9 (a) Photograph of the sample consisting of 0.5-mm-diameter ceramic balls made of Zirconia, which are randomly arranged on a sheet of hard paper and which enable Mie scattering, and (b) schematic of the sample.
and 9(b) show a photograph of the sample and its schematic, respectively. The sample consists of 0.5-mm-diameter ceramic balls made of Zirconia, which are randomly arranged on a sheet of hard paper and enable Mie scattering. In order to monitor the beams, the detector system with the lens L4 (Fig. 1) set on the positioning devices was horizontally and vertically raster-scanned in the plane perpendicular to the optical axis. The scanning range was 60 × 60 mm2 with a center corresponding with the cross point between the optical axis and the scanning plane, and both the horizontal and vertical scanning steps were of 0.5 mm.

First, we monitored the signal beam without the sample by stopping the local oscillator with a beam stopper located between the beam splitters BS2 and BS3 (Fig. 1). Figure 10(a)
Fig. 10 (a) Distribution of the signal beam without the sample, (b) profile along the red line indicated in Fig. 10 (a), (c) distribution of the signal beam with the sample, (d) profile along the red line indicated in Fig. 10 (c), (e) distribution of the local oscillator beam, (f) profile along the red line indicated in Fig. 10 (e), (g) distribution of the mixed beam with the sample, and (h) profile along the red line indicated in Fig. 10 (g)
shows a distribution of the beam intensities in 3D representation viewed from top with colored contour regions. Figure 10(b) shows a line profile along the red line indicated in Fig. 10(a).

Next, we monitored the signal beam by inserting the scattering sample between the lenses L2 and L3. Figures 10(c) and 10(d) show the distribution of beam intensity and the line profile, respectively. From Fig. 10(c), we observe that the distribution appears rough, owing to multiple scattering, and the shape of distribution remarkably changes from that in Fig. 10(a). Further, two peaks are generated, as shown in Fig. 10(d).

Subsequently, we monitored the local oscillator beam by stopping the signal beam with a beam stopper located between the mirror and BS3. Figures 10(e) and 10(f) show the distribution of the beam intensity and the line profile, respectively. Here, in order to clearly demonstrate the effect of selective detection, we intentionally deformed the local oscillator beam profile. As shown in Fig. 10(f), the smaller peaks are observed in the right tail of the main peak.

Finally, we monitored the mixed beam with the sample. Figures 10(g) and 10(h) show the distribution of beam intensity and the line profile, respectively. Comparing Figs. 10(e) and 10(g), we can observe that the distribution of the local oscillator beam resembles that of the mixed beam, while the distribution of the mixed beam appears relatively smooth. Similarly, from Figs. 10(f) and 10(h), the profile of the local oscillator beam resembles that of the mixed beam, while the intensity of the mixed beam is slightly lower than that of the local oscillator beam. The normalized cross-correlation between Figs. 10(e) and 10(g) is 0.821. Although the shape of profile slightly varies by changing the difference in path length between signal and local arms, the normalized cross-correlation between profiles of reference beam and mixed beam falls within the range from 0.75 to 0.85, and the range in the profile of mixed beam where the intensity is not zero is invariant. Thus, the shape of mixed beam greatly receives restriction of the shape of reference beam.

Next, we measured the mixed signals while gradually changing the difference in path length between signal and local arms by translating the reference mirror at a step of 2 μm at the five detector positions, P1 to P5, which are represented as red x-marks on the horizontal lines in Figs. 10(d), 10(f), and 10(h). Figure 11
Fig. 11 Observation of mixed signals, which are measured at positions P1, P2, P3, P4, and P5, which are represented as red x-marks on the horizontal lines in Figs. 10(d), 10(f), and 10(h), while changing the difference in path length between signal and local arms.
shows the mixed signals, where the horizontal and vertical lines are the deference in path length and detected intensity, respectively. We can see that signals oscillate in a sinusoidal manner at P2, P3, and P4, where the intensities of mixed beam are not zero, while no signals are observed at P1 and P5, where the intensities of mixed beam are almost zero. We quantitatively consider the signal at P2. From Figs. 10(d) and 10(f), intensities of reference and signal beams are 0.350 mV and 0.002 mV, respectively. Using these values, ID = 0.352 mV and IA = 0.053 mV from Eqs. (6) and (7), respectively. On the other hand, from Fig. 11, the maximum (M) and minimum (m) of signal at P2 are 0.392 mV and 0.306 mV, respectively. Assuming that the signal is a sinusoidal function while it is distorted because the sample has inhomogeneous regions in refractive index, the center of oscillation and amplitude are obtained as 0.349 mV and 0.0043 mV from (M + m) / 2 and (Mm) / 2, which are regarded as the estimated values of ID and IA, respectively. In spite of the rough assumption that the signal is a sinusoidal function, these values are close to the above values obtained from Eqs. (6) and (7) using experimental data from Fig. 10. Also for signals at P3 and P4, similar results are derived as shown in Table 1

Table 1. Quantitative evaluation of the center of oscillation and amplitude of mixed signal. The second and third columns intensities of local and signal beams obtained from Figs. 10(d) and 10(f), respectively. The fourth and fifth columns are respectively estimated values of the center of oscillation and amplitude using Eqs. (6) and (7). The sixth and seventh columns are respectively maximum and minimum values of sinusoidal signals obtained Fig. 11. The eighth and ninth columns are respectively estimated values of the center of oscillation and amplitude under an assumption that the signals are sinusoidal.

table-icon
View This Table
. From the results, we can see that interference is observed in the region where the intensity of mixed beam is not zero. It addition, the amplitude of mixed signal depends on the intensity of signal beam, and the center of oscillation of mixed signal depends on the intensity of reference beam. Therefore, we can conclude that the interferometer selectively detects only the forward-scattered component, propagating in the same direction as that of the local oscillator beam and preserving the phase information, from among multiply and divergently scattered signal waves emerging from the sample when the signal beam is mixed with the local oscillator beam. This is because the imaging system could quantitatively reproduce the cross section with no remarkable artifacts in spite of the mismatch in the refractive index, as described in Section 4.

Furthermore, the results verify the significant potential as follows: In this research, the imaging system is based on the first-generation CT. This leads to a long data acquisition time, which hampers its practical application. On the other hand, if volumetric parallel beams are available for use as an incident beam and a local oscillator beam, we can obtain a single projection at a time using a 2D detector. Therefore, in order to collect a set of projections required for CT reconstruction, we simply rotate the sample without translation, which results in a drastic reduction in the total data acquisition time. In such an imaging system with a 2D detector, the problem of cross talk is expected to occur. However, the results described above indicate that, if each flux in the volumetric local oscillator beam is parallel to other fluxes, the flux can selectively detect only the forward-scattered component propagating in the same direction as that of the flux from a divergent scattered signal beam. Therefore, we will be possible to obtain a single projection at a time without cross-talk.

6. Conclusion

We proposed a novel THz-CT imaging method based on phase-contrast using a CW source. We constructed a preliminary system for validating the concept. The system acquires the projections of phase-shift using a phase modulation technique with the Mach-Zehnder interferometer and reconstructs the distribution of refractive indices from the measured projections. The experiments using a physical phantom showed effectiveness in that artifact-free quantitative reconstruction was feasible.

The present system has two major problems: One is that the incident intensity in front of a sample is insufficient owing to the use of multiple mirrors and lenses for forming a thin parallel beam. The other is that the total data-acquisition time is very long because the system is based on first-generation CT, in which a set of projection data must be sequentially collected point by point using a thin beam. However, the excellent property of selective detection, which was proved in this study, will surpasses these difficulties. The use of volumetric parallel beams as both signal and local oscillator beams enable us to obtain a single projection at a time by using a 2D detector. Thereby, the data-acquisition time can be drastically reduced. Further, only a few mirrors and lenses are required to form volumetric parallel beams. Our future work will involve construction of a practical system using a volumetric parallel beam and a 2D detector.

References and links

1.

B. B. Hu and M. C. Nuss, “Imaging with terahertz waves,” Opt. Lett. 20(16), 1716–1718 (1995). [CrossRef] [PubMed]

2.

R. M. Woodward, V. P. Wallace, D. D. Arnone, E. H. Linfield, and M. Pepper, “Terahertz pulsed imaging of skin cancer in the time and frequency domain,” J. Biol. Phys. 29(2/3), 257–259 (2003). [CrossRef] [PubMed]

3.

R. Wilk, F. Breitfeld, M. Mikulics, and M. Koch, “Continuous wave terahertz spectrometer as a noncontact thickness measuring device,” Appl. Opt. 47(16), 3023–3026 (2008). [CrossRef] [PubMed]

4.

T. Yasuda, T. Iwata, T. Araki, and T. Yasui, “Improvement of minimum paint film thickness for THz paint meters by multiple-regression analysis,” Appl. Opt. 46(30), 7518–7526 (2007). [CrossRef] [PubMed]

5.

T. Kiwa, J. Kondo, S. Oka, I. Kawayama, H. Yamada, M. Tonouchi, and K. Tsukada, “Chemical sensing plate with a laser-terahertz monitoring system,” Appl. Opt. 47(18), 3324–3327 (2008). [CrossRef] [PubMed]

6.

S. R. Murrill, E. L. Jacobs, S. K. Moyer, C. E. Halford, S. T. Griffin, F. C. De Lucia, D. T. Petkie, and C. C. Franck, “Terahertz imaging system performance model for concealed-weapon identification,” Appl. Opt. 47(9), 1286–1297 (2008). [CrossRef] [PubMed]

7.

Y. Kawada, T. Yasuda, H. Takahashi, and S.-i. Aoshima, “Real-time measurement of temporal waveforms of a terahertz pulse using a probe pulse with a tilted pulse front,” Opt. Lett. 33(2), 180–182 (2008). [CrossRef] [PubMed]

8.

Y. Kawada, T. Yasuda, H. Takahashi, and S. Aoshima, “Real-time measurement of temporal waveforms of a terahertz pulse using a probe pulse with a tilted pulse front,” Opt. Lett. 33(2), 180–182 (2008). [CrossRef] [PubMed]

9.

C. Kak and M. Slanery, “Principles of Computerized Tomographic Imaging,” New York: IEEE Press (1987).

10.

D. M. Mittleman, S. Hunsche, L. Boivin, and M. C. Nuss, “T-ray tomography,” Opt. Lett. 22(12), 904–906 (1997). [CrossRef] [PubMed]

11.

B. Ferguson, S. Wang, D. Gray, D. Abbot, and X. C. Zhang, “T-ray computed tomography,” Opt. Lett. 27(15), 1312–1314 (2002). [CrossRef] [PubMed]

12.

S. Wang, B. Ferguson, and X.-C. Zhang, “Pulsed terahertz tomography,” J. Phys. D Appl. Phys. 37(4), R1–R36 (2004). [CrossRef]

13.

E. Abraham, A. Younus, C. Aguerre, P. Desbarats, and P. Mounaix, “Refraction losses in terahertz computed tomography,” Opt. Commun. 283(10), 2050–2055 (2010). [CrossRef]

14.

D. Porterfield, J. Hesler, T. Crowe, W. Bishop, and D. Woolard, “Integrated terahertz transmit / receive modules,” Proc. of 33rd European Microwave Conference, 1319–1322 (2003).

15.

A. Dobroiu, M. Yamashita, Y. N. Ohshima, Y. Morita, C. Otani, and K. Kawase, “Terahertz imaging system based on a backward-wave oscillator,” Appl. Opt. 43(30), 5637–5646 (2004). [CrossRef] [PubMed]

16.

B. Recur, A. Younus, S. Salort, P. Mounaix, B. Chassagne, P. Desbarats, J.-P. Caumes, and E. Abraham, “Investigation on reconstruction methods applied to 3D terahertz computed tomography,” Opt. Express 19(6), 5105–5117 (2011). [CrossRef] [PubMed]

17.

N. Sunaguchi, Y. Sasaki, N. Maikusa, M. Kawai, T. Yuasa, and C. Otani, “Depth-resolving THz imaging with tomosynthesis,” Opt. Express 17(12), 9558–9570 (2009). [CrossRef] [PubMed]

18.

J. Hsieh, Computed Tomography Principles, Design, Artifacts, and Recent Advances, Second Edition (John Wiley & Sons, Inc. & SPIE, 2009).

19.

S. Feng and H. G. Winful, “Physical origin of the Gouy phase shift,” Opt. Lett. 26(8), 485–487 (2001). [CrossRef] [PubMed]

20.

A. Rosenfeld and C. Kak, Digital Picture Processing, 2nd Ed., Vol. I (Academic Press, 1982).

21.

R. Cusack, J. M. Huntley, and H. T. Goldrein, “Improved noise-immune phase-unwrapping algorithm,” Appl. Opt. 34(5), 781–789 (1995). [CrossRef] [PubMed]

22.

G. Zhao, M. Mors, T. Wenckebach, and P. C. M. Planken, “Terahertz dielectric properties of polystyrene foam,” J. Opt. Soc. Am. B 19(6), 1476–1479 (2002). [CrossRef]

OCIS Codes
(110.6960) Imaging systems : Tomography
(120.3180) Instrumentation, measurement, and metrology : Interferometry
(110.6795) Imaging systems : Terahertz imaging
(110.6955) Imaging systems : Tomographic imaging

ToC Category:
Imaging Systems

History
Original Manuscript: June 6, 2013
Revised Manuscript: September 7, 2013
Manuscript Accepted: October 4, 2013
Published: October 17, 2013

Citation
Masayuki Suga, Yoshiaki Sasaki, Takeshi Sasahara, Tetsuya Yuasa, and Chiko Otani, "THz phase-contrast computed tomography based on Mach-Zehnder interferometer using continuous wave source: proof of the concept," Opt. Express 21, 25389-25402 (2013)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-21-21-25389


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. B. B. Hu and M. C. Nuss, “Imaging with terahertz waves,” Opt. Lett.20(16), 1716–1718 (1995). [CrossRef] [PubMed]
  2. R. M. Woodward, V. P. Wallace, D. D. Arnone, E. H. Linfield, and M. Pepper, “Terahertz pulsed imaging of skin cancer in the time and frequency domain,” J. Biol. Phys.29(2/3), 257–259 (2003). [CrossRef] [PubMed]
  3. R. Wilk, F. Breitfeld, M. Mikulics, and M. Koch, “Continuous wave terahertz spectrometer as a noncontact thickness measuring device,” Appl. Opt.47(16), 3023–3026 (2008). [CrossRef] [PubMed]
  4. T. Yasuda, T. Iwata, T. Araki, and T. Yasui, “Improvement of minimum paint film thickness for THz paint meters by multiple-regression analysis,” Appl. Opt.46(30), 7518–7526 (2007). [CrossRef] [PubMed]
  5. T. Kiwa, J. Kondo, S. Oka, I. Kawayama, H. Yamada, M. Tonouchi, and K. Tsukada, “Chemical sensing plate with a laser-terahertz monitoring system,” Appl. Opt.47(18), 3324–3327 (2008). [CrossRef] [PubMed]
  6. S. R. Murrill, E. L. Jacobs, S. K. Moyer, C. E. Halford, S. T. Griffin, F. C. De Lucia, D. T. Petkie, and C. C. Franck, “Terahertz imaging system performance model for concealed-weapon identification,” Appl. Opt.47(9), 1286–1297 (2008). [CrossRef] [PubMed]
  7. Y. Kawada, T. Yasuda, H. Takahashi, and S.-i. Aoshima, “Real-time measurement of temporal waveforms of a terahertz pulse using a probe pulse with a tilted pulse front,” Opt. Lett.33(2), 180–182 (2008). [CrossRef] [PubMed]
  8. Y. Kawada, T. Yasuda, H. Takahashi, and S. Aoshima, “Real-time measurement of temporal waveforms of a terahertz pulse using a probe pulse with a tilted pulse front,” Opt. Lett.33(2), 180–182 (2008). [CrossRef] [PubMed]
  9. C. Kak and M. Slanery, “Principles of Computerized Tomographic Imaging,” New York: IEEE Press (1987).
  10. D. M. Mittleman, S. Hunsche, L. Boivin, and M. C. Nuss, “T-ray tomography,” Opt. Lett.22(12), 904–906 (1997). [CrossRef] [PubMed]
  11. B. Ferguson, S. Wang, D. Gray, D. Abbot, and X. C. Zhang, “T-ray computed tomography,” Opt. Lett.27(15), 1312–1314 (2002). [CrossRef] [PubMed]
  12. S. Wang, B. Ferguson, and X.-C. Zhang, “Pulsed terahertz tomography,” J. Phys. D Appl. Phys.37(4), R1–R36 (2004). [CrossRef]
  13. E. Abraham, A. Younus, C. Aguerre, P. Desbarats, and P. Mounaix, “Refraction losses in terahertz computed tomography,” Opt. Commun.283(10), 2050–2055 (2010). [CrossRef]
  14. D. Porterfield, J. Hesler, T. Crowe, W. Bishop, and D. Woolard, “Integrated terahertz transmit / receive modules,” Proc. of 33rd European Microwave Conference, 1319–1322 (2003).
  15. A. Dobroiu, M. Yamashita, Y. N. Ohshima, Y. Morita, C. Otani, and K. Kawase, “Terahertz imaging system based on a backward-wave oscillator,” Appl. Opt.43(30), 5637–5646 (2004). [CrossRef] [PubMed]
  16. B. Recur, A. Younus, S. Salort, P. Mounaix, B. Chassagne, P. Desbarats, J.-P. Caumes, and E. Abraham, “Investigation on reconstruction methods applied to 3D terahertz computed tomography,” Opt. Express19(6), 5105–5117 (2011). [CrossRef] [PubMed]
  17. N. Sunaguchi, Y. Sasaki, N. Maikusa, M. Kawai, T. Yuasa, and C. Otani, “Depth-resolving THz imaging with tomosynthesis,” Opt. Express17(12), 9558–9570 (2009). [CrossRef] [PubMed]
  18. J. Hsieh, Computed Tomography Principles, Design, Artifacts, and Recent Advances, Second Edition (John Wiley & Sons, Inc. & SPIE, 2009).
  19. S. Feng and H. G. Winful, “Physical origin of the Gouy phase shift,” Opt. Lett.26(8), 485–487 (2001). [CrossRef] [PubMed]
  20. A. Rosenfeld and C. Kak, Digital Picture Processing, 2nd Ed., Vol. I (Academic Press, 1982).
  21. R. Cusack, J. M. Huntley, and H. T. Goldrein, “Improved noise-immune phase-unwrapping algorithm,” Appl. Opt.34(5), 781–789 (1995). [CrossRef] [PubMed]
  22. G. Zhao, M. Mors, T. Wenckebach, and P. C. M. Planken, “Terahertz dielectric properties of polystyrene foam,” J. Opt. Soc. Am. B19(6), 1476–1479 (2002). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited