MARS pre-clinical imaging: the benefits of small pixels and good energy data

Butler, P. H.; Adebileje, Sikiru A; Alexander, Steven D.; Amma, Maya R; Amjomrouz, Marzieh; Asghariomabad, Fatemeh; Atharifard, Ali; Atlas, James; Bamford, Benjamin; Bell, Stephen T.; Bheesette, S.; Butler, Anthony; Carbonez, Pierre; Chambers, Claire; Chernoglazov, Alexander I.; Clark, Jennifer A.; Crighton, Jonathan S.; Dahal, Shishir; Damet, J.; Ruiter, Niels J A de; Doesburg, R.; Duncan, Neryda; Ghodsian, Nooshin; Gieseg, Steven P.; Goulter, Brian P.; Gurney, Sam; Healy, Joseph L.; Kanithi, Praveenkumar; Kirkbride, Tracy; Lansley, Stuart P.; Lowe, Chiara; Mandalika, V. B. H.; Marfo, Emmanuel; Matanaghi, Aysouda; Moghiseh, Mahdieh; Palmer, David N.; Panta, Raj K.; Prebble, Hannah M.; Raja, Aamir; Sayous, Yann; Renaud, Peter; Schleich, Nanette; Searle, Emily; Sheeja, Jereena S; Uddin, Rayhan; Broeke, Lieza Vanden; Vivek, V.; Walker, E. Peter; Walsh, Michael F.; Wijesooriya, Manoj; Younger, W. Ross

doi:10.1117/12.2532367

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…MARS bio imaging (MBI) are collaborating with several universities in New Zealand (Canterbury, Otago, Lincoln, and Auckland), international research centers and commercial partners [19] to demonstrate applications of the PCD technology. Recent examples include quantifying targeted nanoparticles in bone microfractures [20], identifying suspected hemorrhage in atheroma [21], and differentiating crystals by chemical composition in gout [22]. First preclinical trials are ongoing [23].…”

Section: A Status Of Pcds In Computed Tomographymentioning

confidence: 99%

Photon Counting Detectors for X-Ray Imaging With Emphasis on CT

Ballabriga

Alozy

Bandi³

et al. 2021

IEEE Trans. Radiat. Plasma Med. Sci.

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X-ray imaging is a widely used imaging modality in the medical diagnostic field due to its availability, low cost, high spatial resolution, and fast image acquisition. X-ray photons in standard X-ray sources are polychromatic. Detectors that allow to extract the "color" information of the individual X-rays can lead to contrast enhancement, improved material identification or reduction of beam hardening artifacts at the system level, if we compare them with the widely spread energy integrating detectors. Today, in the field of computed tomography (CT), prototypes of clinical grade systems based on spectral photon counting detectors are currently available for clinical research from different companies. One of the key system components in that development is the X-ray photon detector. This article reviews the photon detection hardware, from the conversion of X-rays into electrical signals to the pulse processing electronics. A review of available photon counting application specific integrated circuits (ASICs) for spectroscopic X-ray imaging is presented with emphasis on the CT medical imaging application.

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Section: A Status Of Pcds In Computed Tomographymentioning

confidence: 99%

Photon Counting Detectors for X-Ray Imaging With Emphasis on CT

Ballabriga

Alozy

Bandi³

et al. 2021

IEEE Trans. Radiat. Plasma Med. Sci.

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show abstract

“…Spectral photon-counting CT is an advanced technique that increases contrast resolution in soft-tissue using novel properties of a photon-counting detector [15,13]. The spectral scanner employed in this study is the MARS spectral CT system (MARS-11 V5.1 (2016) S/N:11, MARS Bioimaging Ltd, New Zealand), which is equipped with the Medipix3RX photon-counting detector [17,18]. The Medipix3RX detector developed at CERN (The European Organization for Nuclear Research) comprises a cadmium zinc telluride semiconductor sensor layer, plus readout electronics for measuring up to eight energies at high resolution (50-200 µm).…”

Section: Introductionmentioning

confidence: 99%

Molecular Imaging of Pulmonary Tuberculosis in an Ex-Vivo Mouse Model Using Spectral Photon-Counting Computed Tomography and Micro-CT

et al. 2021

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Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes

Gennari,

Rossi,

De Cecco

et al. 2024

Int J Cardiovasc Imaging

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Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.

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MARS pre-clinical imaging: the benefits of small pixels and good energy data

Cited by 5 publications

References 16 publications

Photon Counting Detectors for X-Ray Imaging With Emphasis on CT

Photon Counting Detectors for X-Ray Imaging With Emphasis on CT

Molecular Imaging of Pulmonary Tuberculosis in an Ex-Vivo Mouse Model Using Spectral Photon-Counting Computed Tomography and Micro-CT

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes

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