Bio-Inspired Multimodal Imaging in Reduced Visibility

The visual systems found in nature rely on capturing light under different modalities, in terms of spectral sensitivities and polarization sensitivities. Numerous imaging techniques are inspired by this variety, among which, the most famous is color imaging inspired by the trichromacy theory of the human visual system. We investigate the spectral and polarimetric properties of biological imaging systems that will lead to the best performance on scene imaging through haze, i.e., dehazing. We design a benchmark experiment based on modalities inspired by several visual systems, and adapt state-of-the-art image reconstruction algorithms to those modalities. We show the difference in performance of each studied systems and discuss it in front of our methodology and the statistical relevance of our data.

A NIM PET/CT phantom for evaluating the PET image quality of micro-lesions and the performance parameters of CT

Background The commonly used NEMA IEC Body phantom has a number of defects, hindering its application for detecting micro-lesions and measuring the performance parameters of computed tomography (CT). This study aimed to propose a PET/CT phantom designed by National Institute of Metrology (NIM), China, which is capable of simultaneously testing the performance of PET and CT systems, and to evaluate the quality of imaging. Methods The phantom developed in the present study, the NIM PET/CT phantom, is composed of a PET imaging module and a CT imaging module, and these modules are connected together through bolts, which can simultaneously measure the imaging performance of PET and CT systems. Hot spheres were filled with 4:1 sphere-to-background activity concentration using 18F-fluorodeoxyglucose (18F-FDG), and cold spheres were filled with non-radioactive water. We compared the results of imaging obtained from the NIM PET/CT phantom and the NEMA IEC Body phantom to assess their diagnostic efficacy. In order to evaluate the generalization ability of the NIM PET/CT phantom, three different PET/CT systems were used to scan on the same scanning protocol. To evaluate the effects of image reconstruction algorithms on image quality assessment, ordered subset expectation maximization (OSEM), OSEM-point-spread function (PSF), OSEM-TOF, and OSEM-PSF-TOF algorithms were employed. Results The imaging quality of the NIM PET/CT phantom and the NEMA IEC Body phantom was relatively consistent. The NIM PET/CT phantom could detect 7 mm spheres without influencing the imaging quality. It was found that PSF reconstruction exhibited to reduce the speed of convergence, the contrast and background variability of spheres (13–28 mm) were significantly improved after two iterations. In addition to improve the image contrast and background variability, TOF could markedly improve the overall image quality and instrument detection limit. TOF-PSF could noticeably reduce noise level, enhance imaging details, and improve quality of imaging. Conclusions The results showed that in comparison with the NEMA IEC Body phantom, the NIM PET/CT phantom outperformed in evaluating the PET image quality of micro-lesions and the performance parameters of CT.

Harmonization of PET image reconstruction parameters in simultaneous PET/MRI

Objective Simultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data across scanners. In this work, we define image reconstruction parameters that lead to comparable contrast recovery curves across simultaneous PET/MRI systems. Method The NEMA NU-2 image quality phantom was imaged on one GE Signa and on one Siemens mMR PET/MRI scanner. The phantom was imaged at 9.7:1 contrast with standard spheres (diameter 10, 13, 17, 22, 28, 37 mm) and with custom spheres (diameter: 8.5, 11.5, 15, 25, 32.5, 44 mm) using a standardized methodology. Analysis was performed on a 30 min listmode data acquisition and on 6 realizations of 5 min from the listmode data. Images were reconstructed with the manufacturer provided iterative image reconstruction algorithms with and without point spread function (PSF) modeling. For both scanners, a post-reconstruction Gaussian filter of 3–7 mm in steps of 1 mm was applied. Attenuation correction was provided from a scaled computed tomography (CT) image of the phantom registered to the MR-based attenuation images and verified to align on the non-attenuation corrected PET images. For each of these image reconstruction parameter sets, contrast recovery coefficients (CRCs) were determined for the SUVmean, SUVmax and SUVpeak for each sphere. A hybrid metric combining the root-mean-squared discrepancy (RMSD) and the absolute CRC values was used to simultaneously optimize for best match in CRC between the two scanners while simultaneously weighting toward higher resolution reconstructions. The image reconstruction parameter set was identified as the best candidate reconstruction for each vendor for harmonized PET image reconstruction. Results The range of clinically relevant image reconstruction parameters demonstrated widely different quantitative performance across cameras. The best match of CRC curves was obtained at the lowest RMSD values with: for CRCmean, 2 iterations-7 mm filter on the GE Signa and 4 iterations-6 mm filter on the Siemens mMR, for CRCmax, 4 iterations-6 mm filter on the GE Signa, 4 iterations-5 mm filter on the Siemens mMR and for CRCpeak, 4 iterations-7 mm filter with PSF on the GE Signa and 4 iterations-7 mm filter on the Siemens mMR. Over all reconstructions, the RMSD between CRCs was 1.8%, 3.6% and 2.9% for CRC mean, max and peak, respectively. The solution of 2 iterations-3 mm on the GE Signa and 4 iterations-3 mm on Siemens mMR, both with PSF, led to simultaneous harmonization and with high CRC and low RMSD for CRC mean, max and peak with RMSD values of 2.8%, 5.8% and 3.2%, respectively. Conclusions For two commercially available PET/MRI scanners, user-selectable parameters that control iterative updates, image smoothing and PSF modeling provide a range of contrast recovery curves that allow harmonization in harmonization strategies of optimal match in CRC or high CRC values. This work demonstrates that nearly identical CRC curves can be obtained on different commercially available scanners by selecting appropriate image reconstruction parameters.

The Research Progress of Electrical Impedance Tomography for Lung Monitoring

Medical imaging can intuitively show people the internal structure, morphological information, and organ functions of the organism, which is one of the most important inspection methods in clinical medical diagnosis. Currently used medical imaging methods can only be applied to some diagnostic occasions after qualitative lesions have been generated, and the general imaging technology is usually accompanied by radiation and other conditions. However, electrical impedance tomography has the advantages of being noninvasive and non-radiative. EIT (Electrical Impedance Tomography) is also widely used in the early diagnosis and treatment of some diseases because of these advantages. At present, EIT is relatively mature and more and more image reconstruction algorithms are used to improve imaging resolution. Hardware technology is also developing rapidly, and the accuracy of data collection and processing is continuously improving. In terms of clinical application, EIT has also been used for pathological treatment of lungs, the brain, and the bladder. In the future, EIT has a good application prospect in the medical field, which can meet the needs of real-time, long-term monitoring and early diagnosis. Aiming at the application of EIT in the treatment of lung pathology, this article reviews the research progress of EIT, image reconstruction algorithms, hardware system design, and clinical applications used in the treatment of lung diseases. Through the research and introduction of several core components of EIT technology, it clarifies the characteristics of EIT system complexity and its solutions, provides research ideas for subsequent research, and once again verifies the broad development prospects of EIT technology in the future.

Optical breast atlas as a testbed for image reconstruction in optical mammography

We present two optical breast atlases for optical mammography, aiming to advance the image reconstruction research by providing a common platform to test advanced image reconstruction algorithms. Each atlas consists of five individual breast models. The first atlas provides breast vasculature surface models, which are derived from human breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using image segmentation. A finite element-based method is used to deform the breast vasculature models from their natural shapes to generate the second atlas, compressed breast models. Breast compression is typically done in X-ray mammography but also necessary for some optical mammography systems. Technical validation is presented to demonstrate how the atlases can be used to study the image reconstruction algorithms. Optical measurements are generated numerically with compressed breast models and a predefined configuration of light sources and photodetectors. The simulated data is fed into three standard image reconstruction algorithms to reconstruct optical images of the vasculature, which can then be compared with the ground truth to evaluate their performance.

A Modified Exact Reconstruction Algorithm to Determine the Complex Permittivity Perturbations of a Cancer Affected Biological Target using Microwave Tomography Technique

Microwave Tomography Technique (MTT) is an emerging technology that is showing its effectiveness in detecting Cancer at early stage. Due to absolute random and non-deterministic characteristics of Cancer cells, more advancements are required in MTT to accurately detect the presence as well as the location of the affected region. Considering this fundamental issue, in this paper, we have proposed a modified Exact Reconstruction Algorithm (mERA) which is capable enough to provide a detailed analysis of all kinds of complex dielectric perturbations of a cancer affected biological target. In MTT, the detection of presence of a cancerous tumor inside any organ of human body has been done using different image reconstruction algorithms. On the other hand, this algorithm uses a selective data segregation mechanism to generate the perturbed complex cell permittivities of the affected organ tissues. Through this study, it has also been verified that how efficiently our proposed approach can able to detect all types of dielectric variations that may be large (20%), small (5%), positive or may be negative and even in a mixed kind of scenario where affected cells possess the mixture of all types of perturbations simultaneously. As cancerous cell shows peculiar behaviour inside human body and its nature varies from person to person and even in-between different stages (stage 1, stage 2, stage 3, stage 4) of cancer, the algorithm is designed in such a fashion that it can able to detect the presence of tumor considering all such possibilities into account. The results validate its high accuracy and effectiveness in the field of cancer diagnosis.

Evaluation of image reconstruction algorithms in cone-beam computed tomography technique

Cone-beam computed tomography (CBCT) technique is largely used in medical diagnostic imaging and nondestructive materials testing, especially in cases which require fast times and high accuracy level. In this paper, the pros and cons of Feldkamp-Davis-Kress (FDK) and simultaneous iterative reconstruction technique (SIRT) algorithms used in CBCT technique is studied. The method of simulating CBCT systems is also used to provide richer projection data, which helps the research to evaluate many aspects of algorithms.

Radiation Dose Reduction in CT Torsion Measurement of the Lower Limb: Introduction of a New Ultra-Low Dose Protocol

This study analyzed the radiation exposure of a new ultra-low dose (ULD) protocol compared to a high-quality (HQ) protocol for CT-torsion measurement of the lower limb. The analyzed patients (n = 60) were examined in the period March to October 2019. In total, 30 consecutive patients were examined with the HQ and 30 consecutive patients with the new ULD protocol comprising automatic tube voltage selection, automatic exposure control, and iterative image reconstruction algorithms. Radiation dose parameters as well as the contrast-to-noise ratio (CNR) and diagnostic confidence (DC; rated by two radiologists) were analyzed and potential predictor variables, such as body mass index and body volume, were assessed. The new ULD protocol resulted in significantly lower radiation dose parameters, with a reduction of the median total dose equivalent to 0.17 mSv in the ULD protocol compared to 4.37 mSv in the HQ protocol (p < 0.001). Both groups showed no significant differences in regard to other parameters (p = 0.344–0.923). CNR was 12.2% lower using the new ULD protocol (p = 0.033). DC was rated best by both readers in every HQ CT and in every ULD CT. The new ULD protocol for CT-torsion measurement of the lower limb resulted in a 96% decrease of radiation exposure down to the level of a single pelvic radiograph while maintaining good image quality.