Periodic Reporting for period 1 - HI-PHRET (High-resolution Imaging with Phase Retrieved Tomography)
Reporting period: 2019-03-01 to 2021-02-28
Optical tomography, the ability to inspect biological organisms without affecting their functional and vital structures, is an evolving research area that encourages advancement in the study of biological processes.
However, modern measurement methodologies sometimes fail to meet the demands of biomedical imaging. In particular, the process of light diffusion through opaque tissues and problems due to alignments of the experimental setup enormously limit the quality of the results obtainable with conventional microscopy techniques.
In this context, the idea behind the "High-resolution Imaging with Phase Retrieved Tomography" project (HI-PHRET) is to reach the maximum tomographic resolution assisted by an effective imaging pipeline. To do this, we put cutting-edge photonics and computational phase retrieval techniques at the service of the biomedical imaging world.
Mechanical misalignments, light scattering problems, and imaging of objects hidden behind opaque structures were tackled with new implementations of multi-dimensional phase retrieval methods. The project has been structured in three phases, interfacing theory, experiments, and using tailored computational methods:
- We developed a new multi-dimensional and multispectral phase retrieval techniques for the inversion of autocorrelation, by exploiting the computational power offered by GPUs.
- We exploited these methods for the tomographic reconstruction of the fluorescent distribution from biological samples in an optical microscopy setup. Our technique is free from any alignment issues, permits the reconstruction accurate at the sub-pixel level, and achieved a resolution higher than the state-of-art methods.
- Further, we extended the method to perform hidden tomography without the use of lenses, reconstructing samples not directly visible due to the presence of an optically opaque barrier.
However, modern measurement methodologies sometimes fail to meet the demands of biomedical imaging. In particular, the process of light diffusion through opaque tissues and problems due to alignments of the experimental setup enormously limit the quality of the results obtainable with conventional microscopy techniques.
In this context, the idea behind the "High-resolution Imaging with Phase Retrieved Tomography" project (HI-PHRET) is to reach the maximum tomographic resolution assisted by an effective imaging pipeline. To do this, we put cutting-edge photonics and computational phase retrieval techniques at the service of the biomedical imaging world.
Mechanical misalignments, light scattering problems, and imaging of objects hidden behind opaque structures were tackled with new implementations of multi-dimensional phase retrieval methods. The project has been structured in three phases, interfacing theory, experiments, and using tailored computational methods:
- We developed a new multi-dimensional and multispectral phase retrieval techniques for the inversion of autocorrelation, by exploiting the computational power offered by GPUs.
- We exploited these methods for the tomographic reconstruction of the fluorescent distribution from biological samples in an optical microscopy setup. Our technique is free from any alignment issues, permits the reconstruction accurate at the sub-pixel level, and achieved a resolution higher than the state-of-art methods.
- Further, we extended the method to perform hidden tomography without the use of lenses, reconstructing samples not directly visible due to the presence of an optically opaque barrier.
The entire project duration was dedicated to the release of "pyphret", an open-source library with all the image processing tools developed specifically for the project. The software is written in python language and exploits the computational power offered by modern GPU architectures. Furthermore, I have worked in the theoretical formulation of a new image reconstruction method, which I named Anchor-Update. The protocol was applied to produce high-resolution reconstructions of fluorescence distribution within biological specimens. This involved the measurement of the sample with modern selective plane illumination microscopy. Furthermore, I have developed a new setup for hidden tomography, capable of reconstructing three-dimensional objects hidden behind turbid materials.
The outputs of the project comprise four articles in peer-reviewed international journals and four peer-reviewed conference proceedings. At the moment, I have three manuscripts under revision, and I am preparing three drafts to submit in the following period. I was an invited speaker at a conference where I have presented the project. I have participated in three international conferences where I gave four oral presentations. I have attended two summer schools, presenting two posters and one oral seminar. Furthermore, I gave two group seminars, and I was chair and reviewer at an international conference. To wider the audience, the results were disseminated to the public using social media such as Twitter and LinkedIn, with the hashtag #HIPHRET. Before the pandemic, I have participated in the "MeetMe Tonight" event and I was interviewed by a Greek newspaper. I have estimated that the project had collected a total of about twenty thousand interactions during the past two years.
The outputs of the project comprise four articles in peer-reviewed international journals and four peer-reviewed conference proceedings. At the moment, I have three manuscripts under revision, and I am preparing three drafts to submit in the following period. I was an invited speaker at a conference where I have presented the project. I have participated in three international conferences where I gave four oral presentations. I have attended two summer schools, presenting two posters and one oral seminar. Furthermore, I gave two group seminars, and I was chair and reviewer at an international conference. To wider the audience, the results were disseminated to the public using social media such as Twitter and LinkedIn, with the hashtag #HIPHRET. Before the pandemic, I have participated in the "MeetMe Tonight" event and I was interviewed by a Greek newspaper. I have estimated that the project had collected a total of about twenty thousand interactions during the past two years.
The main achievement of the project is the standardization of the autocorrelation as a tool for the tomographic reconstruction. This permits to go beyond the current state of the art reconstruction methods, by removing the needs for data alignment and achieving improved resolution. In particular, this may impact current reconstruction methodologies in the field of optical microscopy, with potential extension to other computed tomography approaches (such as in x-ray or microwave tomography). Currently, the project aimed at biomedical applications, and can be used to monitor the structural/functional development of biomedical specimen for health applications. However, I foresee the possibility of the interest for industrial applications where tomographic reconstructions plays an important role, in particular for the structural inspections of concrete builds, for the health monitoring of tree trunks or for airport security checks.