phase imaging
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2022 ◽  
Vol 150 ◽  
pp. 106833
Author(s):  
Shengyu Lu ◽  
Yong Tian ◽  
Qinnan Zhang ◽  
Xiaoxu Lu ◽  
Jindong Tian

Author(s):  
Fabio Minutoli ◽  
Massimo Russo ◽  
Gianluca Di Bellaearly phase planar imaging ◽  
Riccardo Laudicella ◽  
Alessandro Spataro ◽  
...  

2022 ◽  
Vol 8 (1) ◽  
pp. 6-10
Author(s):  
Krishna Teja Nerella ◽  
Dileep Reddy Ayapaneni ◽  
Surekha Srikonda

Background: Phase images contains information regarding local susceptibility changes between the tissues, which can help measure the iron and other content which changes the local field. Typically, this information is ignored before looking at console. Susceptibility weighted imaging (SWI) is a magnetic resonance (MR) technique detects an early hemorrhagic transformation within the infarct to provide insight into cerebral hemodynamics following the stroke. Objective: Significance of “phase mask imaging in differentiation of hemorrhage and calcifications” in acute stroke patients. Methods: An observational non-interventional study carried out on 100 patients with stroke and headache symptoms. MRI Brain Stroke Profile with FLAIR, DWI, ADC, SWAN, and Phase mask sequences, done on 3T GE MRI scanner. Results: All patients underwent MRI study with SWI sequence. Of 183 cases, 33%(n=60) patients had microbleeds, 5%(n=10) patients had granulomas, 32%(n=58) patients had arterial thrombus with infarct, 11%(n=20) patients had falx calcifications, 11%(n=20) patients had intraparenchymal haemorrhage, and 8%(n=15) patients had infarcts with haemorrhagic transformation. The sensitivity of phase imaging in the detection of calcification was 90%. Conclusion: Phase mask imaging plays an important role to detect intracranial calcifications and chronic microbleeds. Phase mask imaging acts as a supplement tool in acute stroke patients, which guides further management.


2021 ◽  
Vol 13 (4) ◽  
pp. 91
Author(s):  
Arkadiusz Kuś ◽  
Wojciech Krauze ◽  
Małgorzata Kujawińska

In this paper we briefly present the history and outlook on the development of two seemingly distant techniques which may be brought close together with a unified theoretical model described as common k-space theory. This theory also known as the Fourier diffraction theorem is much less common in optical coherence tomography than its traditional mathematical model, but it has been extensively studied in digital holography and, more importantly, optical diffraction tomography. As demonstrated with several examples, this link is one of the important factors for future development of both techniques. Full Text: PDF ReferencesN. Leith, J. Upatnieks, "Reconstructed Wavefronts and Communication Theory", J. Opt. Soc. Am. 52(10), 1123 (1962). CrossRef Y. Park, C. Depeursinge, G. Popescu, "Quantitative phase imaging in biomedicine", Nat. Photonics 12, 578 (2018). CrossRef D. Huang et al., "Optical Coherence Tomography", Science 254(5035), 1178 (1991). CrossRef D. P. Popescu, C. Flueraru, S. Chang, J. Disano, S. Sherif, M.G. Sowa, "Optical coherence tomography: fundamental principles, instrumental designs and biomedical applications", Biophys. Rev. 3(3), 155 (2011). CrossRef M. Wojtkowski, V. Srinivasan, J.G. Fujimoto, T. Ko, J.S. Schuman, A. Kowalczyk, J.S. Duker, "Three-dimensional Retinal Imaging with High-Speed Ultrahigh-Resolution Optical Coherence Tomography", Ophthalmology 112(10), 1734 (2005). CrossRef K.C. Zhou, R. Qian, A.-H. Dhalla, S. Farsiu, J.A. Izatt, "Unified k-space theory of optical coherence tomography", Adv. Opt. Photon. 13(2), 462 (2021). CrossRef A.F. Fercher, C.K. Hitzenberger, G. Kamp, S.Y. El-Zaiat, "Measurement of intraocular distances by backscattering spectral interferometry", Opt. Comm. 117(1-2), 43 (1995). CrossRef E. Wolf, "Determination of the Amplitude and the Phase of Scattered Fields by Holography", J. Opt. Soc. Am. 60(1), 18 (1970). CrossRef E. Wolf, "Three-dimensional structure determination of semi-transparent objects from holographic data", Opt. Comm. 1(4), 153 (1969). CrossRef V. Balasubramani et al., "Roadmap on Digital Holography-Based Quantitative Phase Imaging", J. Imaging 7(12), 252 (2021). CrossRef A. Kuś, W. Krauze, P.L. Makowski, M. Kujawińska, "Holographic tomography: hardware and software solutions for 3D quantitative biomedical imaging (Invited paper)", ETRI J. 41(1), 61 (2019). CrossRef A. Kuś, M. Dudek, M. Kujawińska, B. Kemper, A. Vollmer, "Tomographic phase microscopy of living three-dimensional cell cultures", J. Biomed. Opt. 19(4), 46009 (2014). CrossRef O. Haeberlé, K. Belkebir, H. Giovaninni, A. Sentenac, "Tomographic diffractive microscopy: basics, techniques and perspectives", J. Mod. Opt. 57(9), 686 (2010). CrossRef B. Simon et al., "Tomographic diffractive microscopy with isotropic resolution", Optica 4(4), 460 (2017). CrossRef B.A. Roberts, A.C. Kak, "Reflection Mode Diffraction Tomography", Ultrason. Imag. 7, 300 (1985). CrossRef M. Sarmis et al., "High resolution reflection tomographic diffractive microscopy", J. Mod. Opt. 57(9), 740 (2010). CrossRef L. Foucault et al., "Versatile transmission/reflection tomographic diffractive microscopy approach", J. Opt. Soc. Am. A 36(11), C18 (2019). CrossRef W. Krauze, P. Ossowski, M. Nowakowski, M. Szkulmowski, M. Kujawińska, "Enhanced QPI functionality by combining OCT and ODT methods", Proc. SPIE 11653, 116530B (2021). CrossRef E. Mudry, P.C. Chaumet, K. Belkebir, G. Maire, A. Sentenac, "Mirror-assisted tomographic diffractive microscopy with isotropic resolution", Opt. Lett. 35(11), 1857 (2010). CrossRef P. Hosseini, Y. Sung, Y. Choi, N. Lue, Z. Yaqoob, P. So, "Scanning color optical tomography (SCOT)", Opt. Expr. 23(15), 19752 (2015). CrossRef J. Jung, K. Kim, J. Yoon, Y. Park, "Hyperspectral optical diffraction tomography", Opt. Expr. 24(3), 1881 (2016). CrossRef T. Zhang et al., Biomed. "Multi-wavelength multi-angle reflection tomography", Opt. Expr. 26(20), 26093 (2018). CrossRef R.A. Leitgeb, "En face optical coherence tomography: a technology review [Invited]", Biomed. Opt. Expr. 10(5), 2177 (2019). CrossRef J.F. de Boer, R. Leitgeb, M. Wojtkowski, "Twenty-five years of optical coherence tomography: the paradigm shift in sensitivity and speed provided by Fourier domain OCT [Invited]", Biomed. Opt. Expr. 8(7), 3248 (2017). CrossRef T. Anna, V. Srivastava, C. Shakher, "Transmission Mode Full-Field Swept-Source Optical Coherence Tomography for Simultaneous Amplitude and Quantitative Phase Imaging of Transparent Objects", IEEE Photon. Technol. Lett. 23(11), 899 (2011). CrossRef M.T. Rinehart, V. Jaedicke, A. Wax, "Quantitative phase microscopy with off-axis optical coherence tomography", Opt. Lett. 39(7), 1996 (2014). CrossRef C. Photiou, C. Pitris, "Dual-angle optical coherence tomography for index of refraction estimation using rigid registration and cross-correlation", J. Biomed. Opt. 24(10), 1 (2019). CrossRef Y. Zhou, K.K.H. Chan, T. Lai, S. Tang, "Characterizing refractive index and thickness of biological tissues using combined multiphoton microscopy and optical coherence tomography", Biomed. Opt. Expr. 4(1), 38 (2013). CrossRef K.C. Zhou, R. Qian, S. Degan, S. Farsiu, J.A. Izatt, "Optical coherence refraction tomography", Nat. Photon. 13, 794 (2019). CrossRef


2021 ◽  
Vol 7 (1) ◽  
pp. 3
Author(s):  
Ginevra Begani Provinciali ◽  
Martin Piponnier ◽  
Laura Oudjedi ◽  
Xavier Levecq ◽  
Fabrice Harms ◽  
...  

The Hartman wavefront sensor can be used for X-ray phase imaging with high angular resolution. The Hartmann sensor is able to retrieve both the phase and absorption from a single acquisition. The system calculates the shift in a series of apertures imaged with a detector with respect to their reference positions. In this article, the impact of the reference image on the final image quality is investigated using a laboratory setup. Deflection and absorption images of the same sample are compared using reference images acquired in air and in water. It can be easily coupled with tomographic setups to obtain 3D images of both phase and absorption. Tomographic images of a test sample are shown, where deflection images revealed details that were invisible in absorption. The findings reported in this paper can be used for the improvement of image reconstruction and for expanding the applications of X-ray phase imaging towards materials characterization and medical imaging.


2021 ◽  
Author(s):  
Daniele Pirone ◽  
Joowon Lim ◽  
Francesco Merola ◽  
Lisa Miccio ◽  
Martina Mugnano ◽  
...  

Quantitative Phase Imaging (QPI) has gained popularity because it can avoid the staining step, which in some cases is difficult or impossible. However, QPI does not provide the well-known specificity to various parts of the cell (e.g., organelles, membrane). Here we show a novel computational segmentation method based on statistical inference that bridges the gap between the specificity of Fluorescence Microscopy (FM) and the label-free property of QPI techniques to identify the cell nucleus. We demonstrate application to stain-free cells reconstructed through the holographic learning and in flow cyto-tomography modality. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus-like regions can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal FM data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting the three-dimensional (3D) intracellular specificity directly from the phase-contrast data in a typical flow cytometry configuration.


Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3532
Author(s):  
Jordan E. Hollembeak ◽  
Michael A. Model

Cell volume (CV) regulation is typically studied in short-term experiments to avoid complications resulting from cell growth and division. By combining quantitative phase imaging (by transport-of-intensity equation) with CV measurements (by the exclusion of an external absorbing dye), we were able to monitor the intracellular protein concentration (PC) in HeLa and 3T3 cells for up to 48 h. Long-term PC remained stable in solutions with osmolarities ranging from one-third to almost twice the normal. When cells were subjected to extreme hypoosmolarity (one-quarter of normal), their PC did not decrease as one might expect, but increased; a similar dehydration response was observed at high concentrations of ionophore gramicidin. Highly dilute media, or even moderately dilute in the presence of cytochalasin, caused segregation of water into large protein-free vacuoles, while the surrounding cytoplasm remained at normal density. These results suggest that: (1) dehydration is a standard cellular response to severe stress; (2) the cytoplasm resists prolonged dilution. In an attempt to investigate the mechanism behind the homeostasis of PC, we tested the inhibitors of the protein kinase complex mTOR and the volume-regulated anion channels (VRAC). The initial results did not fully elucidate whether these elements are directly involved in PC maintenance.


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