Optoacoustic (photoacoustic) imaging is an emerging optical imaging modality that combines the rich contrast associated to optical absorption with the ability of ultrasound to provide high-resolution images deep inside tissue. Optoacoustic systems can resolve biologically relevant compounds like haemoglobin species, melanin, lipids, collagen and water, without the use of extrinsically administered contrast agents. The technique has been considered since the late 1970s in imaging applications. However, it is only in recent years that the imaging systems has sufficiently matured to be applied in clinical contexts and produce biomedically relevant images of humans. Most advanced clinical systems combine pure ultrasound and optoacoustic imaging technology and are at the brink of clinical translation. Both techniques produce highly complementary images due to the different nature of their contrast mechanisms. Generally, the ultrasound images provide reference anatomical information while the optoacoustic images provide molecular and functional information. A correct handling of the inverse problem associated to optoacoustic and ultrasound image formation is essential to achieve robust clinical applications. The image formation algorithms still face major challenges that need to be addressed. This research topic is therefore devoted to optoacoustic and ultrasound image formation methods.
Current optoacoustic and ultrasound imaging systems need to address several major issues related to the image formation methods. These include accurate imaging under the influence of limited angle view effects, large computational times required for image formation with high density detector systems, ultrasound propagation and scattering modelling, physical modelling of novel detectors, ill-posed spectral-unmixing in multi-spectral optoacoustic imaging, modelling of the optoacoustic excitation light beam and its propagation in biological tissues, modelling of inhomogeneous acoustic and elastic properties and many others. The goal of this Research Topic is to cover original methods to address these issues. Examples include but are not restricted to: deep learning based reconstruction, compressed sensing, model based reconstruction algorithms, advanced back-projection algorithms (time domain and frequency domain), single detector image reconstruction methods, deep learning based spectral unmixing, etc.
We call for contributions encompassing advances in optoacoustic and ultrasound image formation methods based on new imaging hardware and/or new processing software. Potential contributions include but are not limited to the following topics.
- Machine learning in optoacoustic and ultrasound imaging
- Deep learning in optoacoustic and ultrasound imaging
- Compressed sensing
- Model based reconstruction algorithms
- Advanced delay-and-sum and back-projection algorithms (time domain and frequency domain)
- Single detector image formation methods
- Super-resolution methods
- Signal and image compounding methods
Optoacoustic (photoacoustic) imaging is an emerging optical imaging modality that combines the rich contrast associated to optical absorption with the ability of ultrasound to provide high-resolution images deep inside tissue. Optoacoustic systems can resolve biologically relevant compounds like haemoglobin species, melanin, lipids, collagen and water, without the use of extrinsically administered contrast agents. The technique has been considered since the late 1970s in imaging applications. However, it is only in recent years that the imaging systems has sufficiently matured to be applied in clinical contexts and produce biomedically relevant images of humans. Most advanced clinical systems combine pure ultrasound and optoacoustic imaging technology and are at the brink of clinical translation. Both techniques produce highly complementary images due to the different nature of their contrast mechanisms. Generally, the ultrasound images provide reference anatomical information while the optoacoustic images provide molecular and functional information. A correct handling of the inverse problem associated to optoacoustic and ultrasound image formation is essential to achieve robust clinical applications. The image formation algorithms still face major challenges that need to be addressed. This research topic is therefore devoted to optoacoustic and ultrasound image formation methods.
Current optoacoustic and ultrasound imaging systems need to address several major issues related to the image formation methods. These include accurate imaging under the influence of limited angle view effects, large computational times required for image formation with high density detector systems, ultrasound propagation and scattering modelling, physical modelling of novel detectors, ill-posed spectral-unmixing in multi-spectral optoacoustic imaging, modelling of the optoacoustic excitation light beam and its propagation in biological tissues, modelling of inhomogeneous acoustic and elastic properties and many others. The goal of this Research Topic is to cover original methods to address these issues. Examples include but are not restricted to: deep learning based reconstruction, compressed sensing, model based reconstruction algorithms, advanced back-projection algorithms (time domain and frequency domain), single detector image reconstruction methods, deep learning based spectral unmixing, etc.
We call for contributions encompassing advances in optoacoustic and ultrasound image formation methods based on new imaging hardware and/or new processing software. Potential contributions include but are not limited to the following topics.
- Machine learning in optoacoustic and ultrasound imaging
- Deep learning in optoacoustic and ultrasound imaging
- Compressed sensing
- Model based reconstruction algorithms
- Advanced delay-and-sum and back-projection algorithms (time domain and frequency domain)
- Single detector image formation methods
- Super-resolution methods
- Signal and image compounding methods
