Frontiers in Physics, 2019 An optical phantom model with stable oxygen saturation (StO2) and optical properties (OPs) is the key for quick and accurate calibration of spectral imaging devices.
V. N. Du Le +6 more
doaj +1 more source
Investigation of Collapsed-cone Algorithm Accuracy in Small Fields and Heterogeneous Environments [PDF]
Journal of Biomedical Physics and Engineering, 2021 Background: The use of small fields has increased by the emergence of advanced radiotherapy. Dose calculations of these fields are complex and challenging for many reasons such as lack of electrical equilibrium even in homogeneous environments, and this ...
Razieh Zaghian +4 more
doaj +1 more source
Quantitative magnetic resonance imaging phantoms: A review and the need for a system phantom [PDF]
Magnetic Resonance in Medicine, 2017 The MRI community is using quantitative mapping techniques to complement qualitative imaging. For quantitative imaging to reach its full potential, it is necessary to analyze measurements across systems and longitudinally. Clinical use of quantitative imaging can be facilitated through adoption and use of a standard system phantom, a calibration ...
Kathryn E. Keenan +22 more
openaire +4 more sources
Passive element enriched photoacoustic computed tomography (PER PACT) for simultaneous imaging of acoustic propagation properties and light absorption\ud [PDF]
, 2011 We present a ‘hybrid’ imaging approach which can image both light absorption properties and acoustic transmission properties of an object in a two-dimensional slice using a computed tomography (CT) photoacoustic imager.
Hespen, J.C.G. van +8 more
core +10 more sources
Anthropomorphic Polydimethylsiloxane silicone-based phantom for Diffuse Optical Imaging
Heliyon, 2022 This work presents a method for constructing phantoms suitable for diffuse optical mammography. They are based on Polydimethylsiloxane silicones, with the characteristic of being anthropomorphic, and having similar mechanical and optical properties as a ...
M.V. Waks Serra +8 more
doaj
Anthropomorphic Breast and Head Phantoms for Microwave Imaging [PDF]
Diagnostics, 2018 This paper deals with breast and head phantoms fabricated from 3D-printed structures and liquid mixtures whose complex permittivities are close to that of the biological tissues within a large frequency band. The goal is to enable an easy and safe manufacturing of stable-in-time detailed anthropomorphic phantoms dedicated to the test of microwave ...
Nadine Joachimowicz +3 more
openaire +5 more sources
Influence of wall thickness and diameter on arterial shear wave elastography: a phantom and finite element study [PDF]
, 2017 Quantitative, non-invasive and local measurements of arterial mechanical properties could be highly beneficial for early diagnosis of cardiovascular disease and follow up of treatment.
Bini, Fabiano +6 more
core +1 more source
Heterogeneous Breast Phantom Development for Microwave Imaging Using Regression Models
International Journal of Biomedical Imaging, 2012 As new algorithms for microwave imaging emerge, it is important to have standard accurate benchmarking tests. Currently, most researchers use homogeneous phantoms for testing new algorithms.
Camerin Hahn, Sima Noghanian
doaj +1 more source
Generating Anthropomorphic Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks [PDF]
Med. Phys., 47: 6366-6380 (2020), 2019 Objectives: Computerized phantoms play an essential role in various applications of medical imaging research. Although the existing computerized phantoms can model anatomical variations through organ and phantom scaling, this does not provide a way to fully reproduce anatomical variations seen in humans.
arxiv +1 more source
Real-time markerless tumour tracking with patient-specific deep learning using a personalized data generation strategy: Proof of concept by phantom study [PDF]
Br J Radiol 2020; 93: 20190420, 2020 Objective: For real-time markerless tumour tracking in stereotactic lung radiotherapy, we propose a different approach which uses patient-specific deep learning (DL) using a personalized data generation strategy, avoiding the need for collection of a large patient data set.
arxiv +1 more source