Stereoscopic portable hybrid gamma imaging for source depth estimation

Bugby, Sarah L.; Lees, J.E.; McKnight, W K; Dawood, Numan S.

doi:10.1088/1361-6560/abd955

Cited by 6 publications

(9 citation statements)

References 21 publications

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“…The maximum distance error of 5 mm at a 5-cm source depth appears promising. Bugby et al demonstrated the use of a portable gamma-camera equipped with a pinhole collimator to estimate the source depth based on stereoscopic imaging [ 30 ]. Acquisition of images from different angles could be applied also for the camera used herein, which could possibly give improved accuracy in position estimates from our multi-photopeak method.…”

Section: Discussionmentioning

confidence: 99%

Feasibility of 177Lu activity quantification using a small portable CZT-based gamma-camera

Roth,

Larsson,

Strand

et al. 2024

EJNMMI Phys

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Background In image processing for activity quantification, the end goal is to produce a metric that is independent of the measurement geometry. Photon attenuation needs to be accounted for and can be accomplished utilizing spectral information, avoiding the need of additional image acquisitions. The aim of this work is to investigate the feasibility of 177Lu activity quantification with a small CZT-based hand-held gamma-camera, using such an attenuation correction method. Methods A previously presented dual photopeak method, based on the differential attenuation for two photon energies, is adapted for the three photopeaks at 55 keV, 113 keV, and 208 keV for 177Lu. The measurement model describes the count rates in each energy window as a function of source depth and activity, accounting for distance-dependent system sensitivity, attenuation, and build-up. Parameter values are estimated from characterizing measurements, and the source depth and activity are obtained by minimizing the difference between measured and modelled count rates. The method is applied and evaluated in phantom measurements, in a clinical setting for superficial lesions in two patients, and in a pre-clinical setting for one human tumour xenograft. Evaluation is made for a LEHR and an MEGP collimator. Results For phantom measurements at clinically relevant depths, the average (and standard deviation) in activity errors are 17% ± 9.6% (LEHR) and 2.9% ± 3.6% (MEGP). For patient measurements, deviations from activity estimates from planar images from a full-sized gamma-camera are 0% ± 21% (LEHR) and 16% ± 18% (MEGP). For mouse measurements, average deviations of − 16% (LEHR) and − 6% (MEGP) are obtained when compared to a small-animal SPECT/CT system. The MEGP collimator appears to be better suited for activity quantification, yielding a smaller variability in activity estimates, whereas the LEHR results are more severely affected by septal penetration. Conclusions Activity quantification for 177Lu using the hand-held camera is found to be feasible. The readily available nature of the hand-held camera may enable more frequent activity quantification in e.g., superficial structures in patients or in the pre-clinical setting.

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Section: Discussionmentioning

confidence: 99%

Feasibility of 177Lu activity quantification using a small portable CZT-based gamma-camera

Roth,

Larsson,

Strand

et al. 2024

EJNMMI Phys

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“…The Sentinella 102 places an optical module beside the gamma-imaging module, with images aligned through a calibration process [58]. Stereoscopic imaging, which provides distance information, has also been explored for the Sentinella 102 (optical only) and the HCGC (gamma-optical, including source depth estimation) [58,79]. Example gamma-optical multimodality images are shown in Figure 5.…”

Section: Trends In System Functionalitymentioning

confidence: 99%

“…SLNB has been identified as a suitable clinical application for coded-aperture collimators [93]. A further benefit of codedaperture collimation is that the longitudinal depth of sources within an image can be estimated, as each superimposed projection that makes up the total image is acquired at a different sampling position [9,94], similar to stereoscopic imaging with conventional collimator geometries without the need for multiple images [79]. The addition of sourcedepth information to IGCs provided by coded-aperture collimators is notably valuable for intraoperative radioguidance due to the complexity of many surgical fields.…”

Section: Alternative Collimator Geometriesmentioning

confidence: 99%

Intraoperative Gamma Cameras: A Review of Development in the Last Decade and Future Outlook

Farnworth

Bugby

2023

J. Imaging

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Portable gamma cameras suitable for intraoperative imaging are in active development and testing. These cameras utilise a range of collimation, detection, and readout architectures, each of which can have significant and interacting impacts on the performance of the system as a whole. In this review, we provide an analysis of intraoperative gamma camera development over the past decade. The designs and performance of 17 imaging systems are compared in depth. We discuss where recent technological developments have had the greatest impact, identify emerging technological and scientific requirements, and predict future research directions. This is a comprehensive review of the current and emerging state-of-the-art as more devices enter clinical practice.

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“…The advancements have initiated comprehensive investigations of the DI concept in DL techniques. The most critical challenge towards the application of DL is the absence of datasets that fit the problem [ 110 , 111 , 112 ]. This challenge may also be of great importance for the MDE network.…”

Section: Mde Applying Deep Learning Training Mannersmentioning

confidence: 99%

Monocular Depth Estimation Using Deep Learning: A Review

Masoumian

Rashwan

Cristiano

et al. 2022

Sensors

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In current decades, significant advancements in robotics engineering and autonomous vehicles have improved the requirement for precise depth measurements. Depth estimation (DE) is a traditional task in computer vision that can be appropriately predicted by applying numerous procedures. This task is vital in disparate applications such as augmented reality and target tracking. Conventional monocular DE (MDE) procedures are based on depth cues for depth prediction. Various deep learning techniques have demonstrated their potential applications in managing and supporting the traditional ill-posed problem. The principal purpose of this paper is to represent a state-of-the-art review of the current developments in MDE based on deep learning techniques. For this goal, this paper tries to highlight the critical points of the state-of-the-art works on MDE from disparate aspects. These aspects include input data shapes and training manners such as supervised, semi-supervised, and unsupervised learning approaches in combination with applying different datasets and evaluation indicators. At last, limitations regarding the accuracy of the DL-based MDE models, computational time requirements, real-time inference, transferability, input images shape and domain adaptation, and generalization are discussed to open new directions for future research.

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Stereoscopic portable hybrid gamma imaging for source depth estimation

Cited by 6 publications

References 21 publications

Feasibility of 177Lu activity quantification using a small portable CZT-based gamma-camera

Feasibility of 177Lu activity quantification using a small portable CZT-based gamma-camera

Intraoperative Gamma Cameras: A Review of Development in the Last Decade and Future Outlook

Monocular Depth Estimation Using Deep Learning: A Review

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