A5031377050- Medical Imaging Techniques and Applications
- Advanced X-ray and CT Imaging
- Radiomics and Machine Learning in Medical Imaging
- Cultural Heritage Materials Analysis
- Advanced X-ray Imaging Techniques
- Radiation Dose and Imaging
- Paleopathology and ancient diseases
- Seismic Imaging and Inversion Techniques
- Image Processing and 3D Reconstruction
- Aesthetic Perception and Analysis
- Nuclear Physics and Applications
- Digital Radiography and Breast Imaging
- Enhanced Oil Recovery Techniques
- Pomegranate: compositions and health benefits
- Numerical methods in inverse problems
- Conservation Techniques and Studies
- Reservoir Engineering and Simulation Methods
- Hydraulic Fracturing and Reservoir Analysis
- Drug Solubulity and Delivery Systems
- Tree-ring climate responses
- Dental Radiography and Imaging
- Crystallography and Radiation Phenomena
- Medical Image Segmentation Techniques
- NMR spectroscopy and applications
- Scientific Computing and Data Management
Centrum Wiskunde & Informatica
2017-2023
University of Manchester
2015-2023
College of Western Idaho
2018-2019
Akdeniz University
2017-2018
Akdeniz University Hospital
2017
Bethany College - West Virginia
2017
Sparsity regularization (SR) such as total variation (TV) minimization allows accurate image reconstruction in x-ray computed tomography (CT) from fewer projections than analytical methods. Exactly how few suffice and this number may depend on the remain poorly understood. Compressive sensing connects critical of to sparsity, but does not cover CT, however empirical results suggest a similar connection. The present work establishes for real CT data connection between gradient sparsity...
In tomographic imaging, the traditional process consists of an expert and operator collecting data, working on reconstructed slices drawing conclusions. The quality reconstructions depends heavily collected except that, in has very little influence over acquisition parameters, experimental plan or data. It is often case that to draw limited conclusions from reconstructions, adapt a research question data available. This method imaging static sequential, limits potential tomography as tool....
The reconstruction of computed tomography (CT) images is an active area research. Following the rise deep learning methods, many data-driven models have been proposed in recent years. In this work, we present results a data challenge that organized, bringing together algorithm experts from different institutes to jointly work on quantitative evaluation several methods two large, public datasets during ten day sprint. We focus applications CT, namely, low-dose CT and sparse-angle CT. This...
Computed Tomography (CT) has proven itself as a powerful technique for analysing the internal structure of cultural heritage objects. The process followed by conservators and technical art historians investigating an object is explorative: each time new question asked based on outcome previous investigation. This workflow however conflicts with static nature CT imaging, where planning, execution image analysis single scan can take days, or even weeks. A often requires conducting experiment,...
Abstract. A variable volume flow cell has been integrated with state-of-the-art ultra-high-speed synchrotron X-ray tomography imaging. The combination allows the first real-time (sub-second) capture of dynamic pore (micron)-scale fluid transport processes in 4-D (3-D + time). With 3-D data volumes acquired at up to 20 Hz, we perform situ experiments that high-frequency pore-scale dynamics 5–25 mm diameter samples voxel equivalent a pixel) resolutions 2.5 3.8 µm. are free from motion...
Abstract Structural polymeric materials incorporating a microencapsulated liquid healing agent demonstrate the ability to autonomously heal cracks. Understanding how an advancing crack interacts with microcapsules is critical optimizing performance through tailoring size, distribution and density of these capsules. For first time, time-lapse synchrotron X-ray phase contrast computed tomography (CT) has been used observe in three-dimensions (3D) dynamic process growth, microcapsule rupture...
Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consisting of measurement data and ground-truth images. However, suitable experimental X-ray Computed Tomography (CT) are scarce, methods often developed evaluated only simulated data. We fill this gap by providing the community with a versatile, open 2D fan-beam CT dataset ML range reconstruction tasks. To acquire it,...
Abstract Dendrochronology is an essential tool to determine the date and provenance of wood from historical art objects. As standard methods access tree rings are invasive, X-ray computed tomography (CT) has been proposed for non-invasive dendrochronological investigation. While traditional CT can provide clear images inner structure wooden objects, it requires their full rotation, imposing strong limitations on size object. These have previously encouraged investigations into alternative...
Unlike previous works, this open data collection consists of X-ray cone-beam (CB) computed tomography (CT) datasets specifically designed for machine learning applications and high cone-angle artefact reduction. Forty-two walnuts were scanned with a laboratory set-up to provide not only from single object but class objects natural variability. For each walnut, CB projections on three different source orbits acquired cone angles as well being able compute artefact-free, high-quality ground...
The appraisal of the design and weaving structure Islamic knotted-pile carpets can tell plenty about context in which they were produced, identification signs deterioration help to establish their condition. These are often somewhat imprecise laborious examinations, especially when considering large dimensions. Analytical methods that support these disciplines urge further exploration so improved interpretations be obtained. An interdisciplinary combination art history, analytical science...
Studying the wood of art objects such as sculptures, panel paintings and furniture can be crucial to elucidate their chronology production centre. Here we present an approach that considers provenance its potential availability in different areas a means identify wooden objects. We illustrate this with interdisciplinary study aimed determine date Woman lantern, carved altar fragment from Rijksmuseum's collections (Amsterdam, The Netherlands). origin object is undocumented, but based on...
Dating the wood from historical art objects is a crucial step to ascertain their production time, and support or refute attribution an artist workshop. Dendrochronology commonly used for this purpose but requires access tree-ring pattern in wood, which can be hindered by preparatory layers, polychromy, wax, integrated frames. Here we implemented non-invasive dendrochronology based on X-ray computed tomography (CT) examine painting panel attributed Rubens' studio its presumed dating around...
Abstract Real-time X-ray tomography pipelines, such as implemented by RECAST3D, compute and visualize tomographic reconstructions in milliseconds, enable the observation of dynamic experiments synchrotron beamlines laboratory scanners. For extending real-time reconstruction image processing analysis components, Deep Neural Networks (DNNs) are a promising technology, due to their strong performance much faster run-times compared conventional algorithms. DNNs may prevent experiment repetition...
In tomography, the resolution of reconstructed 3D volume is inherently limited by pixel detector and optical phenomena. Machine learning has demonstrated powerful capabilities for super-resolution in several imaging applications. Such methods typically rely on availability high-quality training data a series similar objects. many applications existing machine cannot be used because scanning such objects either impossible or infeasible. this paper, we propose novel technique improving...
Abstract Covered tightly by a thin leather skin, three early seventeenth-century cornetts from the collection of Rijksmuseum were examined with focus on their construction and manufacturing. One cornett unexpectedly turned out to have peculiar be made two sections different wood species. The question arose whether this could original or is result an extensive restoration. As internal structure not accessible for analysis examination, multi-scale Computed Tomography (CT) scanning was employed...
The initial release of the codes, to be used for SophiaBeads Dataset Project. The codes are essential work with Dataset. contains scripts loading dataset, pre-reconstruction steps, and a reconstruction algorithm (cgls_XTek) as template. More information about this can found on GitHub project page. SophiaBeads Project: https://zenodo.org/record/16474
Abstract Conventionally the performance of computed tomography (CT) reconstruction algorithms is assessed by a voxel-to-voxel comparison between object and reconstructed volume, often using digital phantoms. However real aim in CT imaging community not to develop algorithm obtain best-looking images, but one that allows us extract relevant information desired accuracy. Here, through various case studies, we quantify features interest for test use these as measures efficacy reconstructions....
A driving force for the development of new reconstruction algorithms is to achieve better quality images using less information (lower dose, fewer projections, in time), but under what circumstances do iterative methods become worth effort? In this paper we propose a framework that enables performance be mapped. Such allows fair comparisons made, providing insights into experimental acquisition strategies and quantifying reconstructions, identifying sweet spot different algorithms.