31 research outputs found
Reconstruction as a service: a data space for off-site image reconstruction in magnetic particle imaging
Magnetic particle imaging (MPI) is an emerging medical imaging modality which
offers a unique combination of high temporal and spatial resolution,
sensitivity and biocompatibility. For system-matrix (SM) based image
reconstruction in MPI, a huge amount of calibration data needs to be acquired
prior to reconstruction in a time-consuming procedure. Conventionally, the data
is recorded on-site inside the scanning device, which significantly limits the
time that the scanning device is available for patient care in a clinical
setting. Due to its size, handling the calibration data can be challenging. To
solve these issues of recording and handling the data, data spaces could be
used, as it has been shown that the calibration data can be measured in
dedicated devices off-site. We propose a data space aimed at improving the
efficiency of SM-based image reconstruction in MPI. The data space consists of
imaging facilities, calibration data providers and reconstruction experts. Its
specifications follow the reference architecture model of international data
spaces (IDS). Use-cases of image reconstruction in MPI are formulated. The
stakeholders and tasks are listed and mapped to the terminology of IDS. The
signal chain in MPI is analysed to identify a minimum information model which
is used by the data space
Towards Picogram Detection of Superparamagnetic Iron-Oxide Particles Using a Gradiometric Receive Coil
Superparamagnetic iron-oxide nanoparticles can be used in a variety of
medical applications like vascular or targeted imaging. Magnetic particle
imaging (MPI) is a promising tomographic imaging technique that allows
visualizing the 3D nanoparticle distribution concentration in a non-invasive
manner. The two main strengths of MPI are high temporal resolution and high
sensitivity. While the first has been proven in the assessment of dynamic
processes like cardiac imaging, it is unknown how far the detection limit of
MPI can be lowered. Within this work, we will present a highly sensitive
gradiometric receive-coil unit combined with a noise-matching network tailored
for the measurement of mice. The setup is capable of detecting 5 ng of iron in
vitro at 2.14 sec acquisition time. In terms of iron concentration we are able
to detect 156 {\mu}g/L marking the lowest value that has been reported for an
MPI scanner so far. In vivo MPI mouse images of a 512 ng bolus at 21.5 ms
acquisition time allow for capturing the flow of an intravenously injected
tracer through the heart of a mouse. Since it has been rather difficult to
compare detection limits across MPI publications we propose guidelines
improving the comparability of future MPI studies.Comment: 15 Pages, 7 Figures, V2: Changed the initials of Author Kannan M
Krishnan, added two citations, corrected typo
On the reproducibility of extrusion-based bioprinting: round robin study on standardization in the field
The outcome of three-dimensional (3D) bioprinting heavily depends, amongst others, on the interaction between the developed bioink, the printing process, and the printing equipment. However, if this interplay is ensured, bioprinting promises unmatched possibilities in the health care area. To pave the way for comparing newly developed biomaterials, clinical studies, and medical applications (i.e. printed organs, patient-specific tissues), there is a great need for standardization of manufacturing methods in order to enable technology transfers. Despite the importance of such standardization, there is currently a tremendous lack of empirical data that examines the reproducibility and robustness of production in more than one location at a time. In this work, we present data derived from a round robin test for extrusion-based 3D printing performance comprising 12 different academic laboratories throughout Germany and analyze the respective prints using automated image analysis (IA) in three independent academic groups. The fabrication of objects from polymer solutions was standardized as much as currently possible to allow studying the comparability of results from different laboratories. This study has led to the conclusion that current standardization conditions still leave room for the intervention of operators due to missing automation of the equipment. This affects significantly the reproducibility and comparability of bioprinting experiments in multiple laboratories. Nevertheless, automated IA proved to be a suitable methodology for quality assurance as three independently developed workflows achieved similar results. Moreover, the extracted data describing geometric features showed how the function of printers affects the quality of the printed object. A significant step toward standardization of the process was made as an infrastructure for distribution of material and methods, as well as for data transfer and storage was successfully established
On the reproducibility of extrusion-based bioprinting: round robin study on standardization in the field
The outcome of three-dimensional (3D) bioprinting heavily depends, amongst others, on the interaction between the developed bioink, the printing process, and the printing equipment. However, if this interplay is ensured, bioprinting promises unmatched possibilities in the health care area. To pave the way for comparing newly developed biomaterials, clinical studies, and medical applications (i.e. printed organs, patient-specific tissues), there is a great need for standardization of manufacturing methods in order to enable technology transfers. Despite the importance of such standardization, there is currently a tremendous lack of empirical data that examines the reproducibility and robustness of production in more than one location at a time. In this work, we present data derived from a round robin test for extrusion-based 3D printing performance comprising 12 different academic laboratories throughout Germany and analyze the respective prints using automated image analysis (IA) in three independent academic groups. The fabrication of objects from polymer solutions was standardized as much as currently possible to allow studying the comparability of results from different laboratories. This study has led to the conclusion that current standardization conditions still leave room for the intervention of operators due to missing automation of the equipment. This affects significantly the reproducibility and comparability of bioprinting experiments in multiple laboratories. Nevertheless, automated IA proved to be a suitable methodology for quality assurance as three independently developed workflows achieved similar results. Moreover, the extracted data describing geometric features showed how the function of printers affects the quality of the printed object. A significant step toward standardization of the process was made as an infrastructure for distribution of material and methods, as well as for data transfer and storage was successfully established
GAN-based deblurring of reconstructed images for MPI
Reconstructed images may suffer from blurring and reconstruction artefacts in Magnetic Particle Imaging. In this work, a generative adversarial network is used for deblurring reconstructed images in a post-processing step. The network is trained using eigen-reconstructions of a system matrix and evaluated on synthesized phantoms
Recovering higher harmonics when increasing the frame rate in MPI
The frame rate of an MPI measurement can be increased by splitting the receive signal and reconstructing the split signals separately. Thus, motion artefacts can be reduced. Splitting the signal results in a decreased spectral resolution and a mismatch of higher harmonics. In this contribution, an approach for recovering the spectral resolution and higher harmonics is shown that is based on mirroring the split signals
SNR and Discretization Enhancement for System Matrix Determination by Decreasing the Gradient in Magnetic Particle Imaging
In system matrix (SM) based reconstruction, the physical resolution is often within the range of the SM discretization. This is caused by the signal to noise ratio (SNR) decrease following a discretization increase due to the smaller particle sample volume. As the SNR affects the resolution of the image as well, it is necessary to decouple the SNR and discretization. In this work, a calibration protocol is presented which enhances either the SNR or discretization by reducing the gradient strength within the system calibration. This new protocol results in higher resolution and better image quality