A comprehensive review on Compton camera image reconstruction: from principles to AI innovations.

Compton cameras have emerged as promising tools in biomedical imaging, offering sensitive gamma-ray imaging capabilities for diverse applications. This review paper comprehensively overviews the latest advancements in Compton camera image reconstruction technologies. Beginning with a discussion of the fundamental principles of Compton scattering and its relevance to gamma-ray imaging, the paper explores the key components and design considerations of Compton camera systems.

Comparative study on gamma-ray detectors for in-situ ocean radiation monitoring system.

Large-sized crystals and state-of-the-art photosensors are desirable to cope with low environmental radioactivity (e.g., 1-2 Bq∙mCs in surface seawater) for homeland security purposes.

Underwater Optical-Sonar Image Fusion Systems.

Unmanned underwater operations using remotely operated vehicles or unmanned surface vehicles are increasing in recent times, and this guarantees human safety and work efficiency. Optical cameras and multi-beam sonars are generally used as imaging sensors in underwater environments. However, the obtained underwater images are difficult to understand intuitively, owing to noise and distortion.

Temporal Prediction of Paralytic Shellfish Toxins in the Mussel Using a LSTM Neural Network Model from Environmental Data.

Paralytic shellfish toxins (PSTs) are produced mainly by (formerly ). Since 2000, the National Institute of Fisheries Science (NIFS) has been providing information on PST outbreaks in Korean coastal waters at one- or two-week intervals. However, a daily forecast is essential for immediate responses to PST outbreaks.

High Spatial-Resolution Red Tide Detection in the Southern Coast of Korea Using U-Net from PlanetScope Imagery.

Red tides caused by occur continuously along the southern coast of Korea, where there are many aquaculture cages, and therefore, prompt monitoring of bloom water is required to prevent considerable damage. Satellite-based ocean-color sensors are widely used for detecting red tide blooms, but their low spatial resolution restricts coastal observations. Contrarily, terrestrial sensors with a high spatial resolution are good candidate sensors, despite the lack of spectral resolution and bands for red tide detection.

Analytic simulator and image generator of multiple-scattering Compton camera for prompt gamma ray imaging.

For prompt gamma ray imaging for biomedical applications and environmental radiation monitoring, we propose herein a multiple-scattering Compton camera (MSCC). MSCC consists of three or more semiconductor layers with good energy resolution, and has potential for simultaneous detection and differentiation of multiple radio-isotopes based on the measured energies, as well as three-dimensional (3D) imaging of the radio-isotope distribution. In this study, we developed an analytic simulator and a 3D image generator for a MSCC, including the physical models of the radiation source emission and detection processes that can be utilized for geometry and performance prediction prior to the construction of a real system.

FPGA-Based Interface of Digital DAQ System for Double-Scattering Compton Camera.

Purpose: The double-scattering Compton camera (DSCC) is a radiation imaging system that can provide both unknown source energy spectra and 3D spatial source distributions. The energies and detection locations measured in coincidence with three CdZnTe (CZT) detectors contribute to reconstructing emission energies and a spatial image based on conical surface integrals. In this study, we developed a digital data acquisition (DAQ) board to support our research into coincidence detection in the DSCC.

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties.

Extremely low-dose CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This work explores the use of knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map.

Comparison Between Pre-Log and Post-Log Statistical Models in Ultra-Low-Dose CT Reconstruction.

X-ray detectors in clinical computed tomography (CT) usually operate in current-integrating mode. Their complicated signal statistics often lead to intractable likelihood functions for practical use in model-based image reconstruction (MBIR). It is therefore desirable to design simplified statistical models without losing the essential factors.

Mixed Confidence Estimation for Iterative CT Reconstruction.

Dynamic (4D) CT imaging is used in a variety of applications, but the two major drawbacks of the technique are its increased radiation dose and longer reconstruction time. Here we present a statistical analysis of our previously proposed Mixed Confidence Estimation (MCE) method that addresses both these issues. This method, where framed iterative reconstruction is only performed on the dynamic regions of each frame while static regions are fixed across frames to a composite image, was proposed to reduce computation time.

Mixed Confidence Estimation for Iterative CT Reconstruction.

We present a statistical analysis of our previously proposed Constrain-Static Target-Kinetic algorithm for 4D CT reconstruction. This method, where framed iterative reconstruction is only performed on the dynamic regions of each frame, while static regions are fixed across frames to a composite image, was proposed to reduce computation time. In this work, we generalize the previous method to describe any application where a portion of the image is known with higher confidence (static, composite, lower-frequency content, etc.

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties.

Extremely low-dose CT acquisitions for the purpose of PET attenuation correction will have a high level of noise and biasing artifacts due to factors such as photon starvation. This work explores a priori knowledge appropriate for CT iterative image reconstruction for PET attenuation correction. We investigate the maximum a posteriori (MAP) framework with cluster-based, multinomial priors for the direct reconstruction of the PET attenuation map.

Resolution recovery reconstruction for a Compton camera.

The spatial resolution from Compton cameras suffers from measurement uncertainties in interaction positions and energies. The degree of degradation in spatial resolution is shift-variant (SV) over the field-of-view (FOV) because the imaging principle is based on the conical surface integration. In our study, the shift-variant point spread function (SV-PSF) is derived from point source measurements at various positions in the FOV and is incorporated into the system matrix of a fully three-dimensional, accelerated reconstruction, i.

Gap compensation during PET image reconstruction by constrained, total variation minimization.

Purpose: Positron emission tomography (PET) is a noninvasive molecular imaging tool with various clinical and preclinical applications. The polygonal structure of small-diameter PET scanners that are designed for specific purposes can lead to gaps between the detector modules and result in loss of PET data during measurement. In the current study, the authors applied the compressed sensing (CS)-based total variation (TV) minimization method to PET image reconstructions to reduce the artifacts caused by gaps in small-diameter PET systems.

Fully three-dimensional OSEM-based image reconstruction for Compton imaging using optimized ordering schemes.

Although the ordered subset expectation maximization (OSEM) algorithm does not converge to a true maximum likelihood solution, it is known to provide a good solution if the projections that constitute each subset are reasonably balanced. The Compton scattered data can be allocated to subsets using scattering angles (SA) or detected positions (DP) or a combination of the two (AP (angles and positions)). To construct balanced subsets, the data were first arranged using three ordering schemes: the random ordering scheme (ROS), the multilevel ordering scheme (MLS) and the weighted-distance ordering scheme (WDS).