About this Research Topic
Liquid biopsy has recently emerged as a non-invasive, repeatable, and potentially low-cost alternative to tissue biopsy. These so-called liquid biopsies refer generally to a patient’s bodily fluids including; blood, urine, and ascites. Identifying the presence and subsequently assessing the character of cancerous cells which have left primary or even metastatic tumors using liquid biopsy has shown great utility for improving patient care including; enabling early cancer detection, determining patient prognosis, and directing longitudinal treatments. More recently, a promising optical, label-free, and high-throughput technology involving digital holography microscopy, microfluidics, and artificial intelligence has been developed to identify cancer cells in the bulk flow. This approach will enable the rapid analysis of liquid biopsy samples from cancer patients and can be investigated further to aid the development of novel protocols for managing cancer patients.
In the aforementioned integration technique, the cells flow through a microfluidic channel and are subsequently imaged at a high frame rate. These cells appear as roundish objects in individual frames of phase reconstruction maps. Primarily, a portable digital holographic microscopy module with microfluidic channels has significant medical applications. In numerical reconstruction, the reduction of speckle noise, phase aberrations, and phase unwrapping has to be dealt with in real-time. Secondly, holographic tomography allows the reconstruction of the 3D refractive index distribution of a cell. However, in these cases, no prior information regarding the 3D orientation of the cell is available, and, therefore, a tracking based rolling-angles recovery method is required. Thirdly, quantitative phase signatures can be used to classify cells, raising the question of whether altered phase signatures can be linked to specific biological functions. Finally, artificial intelligence could be utilized to enhance the utility of holographic imaging by distinguishing medically relevant cell features.
This Research Topic aims to collect representative works, either original research or review papers, from experts across the field, with the aim of providing insights into recent developments in this area, as well as reporting on existing methodologies and emerging technologies that are expected to have a significant impact in this field.
Topics of particular interest include, but are not limited to:
- Digital holographic reconstruction
- Numerical aberration compensation
- Speckle noise reduction
- Holographic tomography
- Cell classification based on artificial technique
In the aforementioned integration technique, the cells flow through a microfluidic channel and are subsequently imaged at a high frame rate. These cells appear as roundish objects in individual frames of phase reconstruction maps. Primarily, a portable digital holographic microscopy module with microfluidic channels has significant medical applications. In numerical reconstruction, the reduction of speckle noise, phase aberrations, and phase unwrapping has to be dealt with in real-time. Secondly, holographic tomography allows the reconstruction of the 3D refractive index distribution of a cell. However, in these cases, no prior information regarding the 3D orientation of the cell is available, and, therefore, a tracking based rolling-angles recovery method is required. Thirdly, quantitative phase signatures can be used to classify cells, raising the question of whether altered phase signatures can be linked to specific biological functions. Finally, artificial intelligence could be utilized to enhance the utility of holographic imaging by distinguishing medically relevant cell features.
This Research Topic aims to collect representative works, either original research or review papers, from experts across the field, with the aim of providing insights into recent developments in this area, as well as reporting on existing methodologies and emerging technologies that are expected to have a significant impact in this field.
Topics of particular interest include, but are not limited to:
- Digital holographic reconstruction
- Numerical aberration compensation
- Speckle noise reduction
- Holographic tomography
- Cell classification based on artificial technique
Keywords: Quantitative phase imaging, Tomographic phase microscopy, Artificial Intelligence, Digital holography, Liquid biopsy, Lab-on-chip
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