Records |
Author |
Albiol, F.; Corbi, A.; Albiol, A. |
Title |
Geometrical Calibration of X-Ray Imaging With RGB Cameras for 3D Reconstruction |
Type |
Journal Article |
Year |
2016 |
Publication |
IEEE Transactions on Medical Imaging |
Abbreviated Journal |
IEEE Trans. Med. Imaging |
Volume |
35 |
Issue |
8 |
Pages |
1952-1961 |
Keywords |
3D reconstruction; camera system; geometric calibration; visible fiducials; X-ray imaging |
Abstract |
We present a methodology to recover the geometrical calibration of conventional X-ray settings with the help of an ordinary video camera and visible fiducials that are present in the scene. After calibration, equivalent points of interest can be easily identifiable with the help of the epipolar geometry. The same procedure also allows the measurement of real anatomic lengths and angles and obtains accurate 3D locations from image points. Our approach completely eliminates the need for X-ray-opaque reference marks (and necessary supporting frames) which can sometimes be invasive for the patient, occlude the radiographic picture, and end up projected outside the imaging sensor area in oblique protocols. Two possible frameworks are envisioned: a spatially shifting X-ray anode around the patient/object and a moving patient that moves/rotates while the imaging system remains fixed. As a proof of concept, experiences with a device under test (DUT), an anthropomorphic phantom and a real brachytherapy session have been carried out. The results show that it is possible to identify common points with a proper level of accuracy and retrieve three-dimensional locations, lengths and shapes with a millimetric level of precision. The presented approach is simple and compatible with both current and legacy widespread diagnostic X-ray imaging deployments and it can represent a good and inexpensive alternative to other radiological modalities like CT. |
Address |
[Albiol, Francisco; Corbi, Alberto] Univ Valencia, Consejo Super Invest Cient, Inst Fis Corpuscular IFIC, Paterna 46980, Spain, Email: kiko@ific.uv.es; |
Corporate Author |
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Thesis |
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Publisher |
Ieee-Inst Electrical Electronics Engineers Inc |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0278-0062 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
|
Notes |
WOS:000381436000016 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
2781 |
Permanent link to this record |
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Author |
Caballero, L.; Albiol, F.; Corbi Bellot, A.; Domingo-Pardo, C.; Leganes Nieto, J.L.; Agramunt Ros, J.; Contreras, P.; Monserrate, M.; Olleros Rodriguez, P.; Perez Magan, D.L. |
Title |
Gamma-ray imaging system for real-time measurements in nuclear waste characterisation |
Type |
Journal Article |
Year |
2018 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
Volume |
13 |
Issue |
|
Pages |
P03016 - 23pp |
Keywords |
Inspection with gamma rays; Radiation monitoring |
Abstract |
Acompact, portable and large field-of-viewgamma camera that is able to identify, locate and quantify gamma-ray emitting radioisotopes in real-time has been developed. The device delivers spectroscopic and imaging capabilities that enable its use it in a variety of nuclear waste characterisation scenarios, such as radioactivity monitoring in nuclear power plants and more specifically for the decommissioning of nuclear facilities. The technical development of this apparatus and some examples of its application in field measurements are reported in this article. The performance of the presented gamma-camera is also benchmarked against other conventional techniques. |
Address |
[Caballero, L.] Univ Valencia, CSIC, Inst Fis Corpuscular, C Catedrat Jose Beltran 2, E-46980 Paterna, Spain, Email: Luis.Caballero@ific.uv.es |
Corporate Author |
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Thesis |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000428146300006 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
3540 |
Permanent link to this record |
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Author |
Magan, D.L.P.; Caballero, L.; Domingo-Pardo, C.; Agramunt-Ros, J.; Albiol, F.; Casanovas, A.; Gonzalez, A.; Guerrero, C.; Lerendegui-Marco, J.; Tarifeño-Saldivia, A. |
Title |
First tests of the applicability of gamma-ray imaging for background discrimination in time-of-flight neutron capture measurements |
Type |
Journal Article |
Year |
2016 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
Volume |
823 |
Issue |
|
Pages |
107-119 |
Keywords |
Neutron capture cross-sections; gamma-ray imaging; Total energy detectors; Pulse-height weighting technique; Time-of-flight method |
Abstract |
In this work we explore for the first time the applicability of using gamma-ray imaging in neutron capture measurements to identify and suppress spatially localized background. For this aim, a pinhole gamma camera is assembled, tested and characterized in terms of energy and spatial performance. It consists of a monolithic CeBr3 scintillating crystal coupled to a position-sensitive photomultiplier and readout through an integrated circuit AMIC2GR. The pinhole collimator is a massive carven block of lead. A series of dedicated measurements with calibrated sources and with a neutron beam incident on a Au-197 sample have been carried out at n_TOF, achieving an enhancement of a factor of two in the signal-to-background ratio when selecting only those events coming from the direction of the sample. |
Address |
[Perez Magan, D. L.; Caballero, L.; Domingo-Pardo, C.; Agramunt-Ros, J.; Albiol, F.; Tarifeno-Saldivia, A.] Univ Valencia, CSIC, IFIC, E-46071 Valencia, Spain, Email: domingo@ific.uv.es |
Corporate Author |
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Thesis |
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Publisher |
Elsevier Science Bv |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0168-9002 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
|
Notes |
WOS:000374661600015 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
2665 |
Permanent link to this record |
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Author |
Real, D.; Calvo, D.; Zornoza, J.D.; Manzaneda, M.; Gozzini, R.; Ricolfe-Viala, C.; Lajara, R.; Albiol, F. |
Title |
Fast Coincidence Filter for Silicon Photomultiplier Dark Count Rate Rejection |
Type |
Journal Article |
Year |
2024 |
Publication |
Sensors |
Abbreviated Journal |
Sensors |
Volume |
24 |
Issue |
7 |
Pages |
2084 - 12pp |
Keywords |
time-to-digital converters; neutrino telescopes; silicon photomultipliers; dark noise rate filtering |
Abstract |
Silicon Photomultipliers find applications across various fields. One potential Silicon Photomultiplier application domain is neutrino telescopes, where they may enhance the angular resolution. However, the elevated dark count rate associated with Silicon Photomultipliers represents a significant challenge to their widespread utilization. To address this issue, it is proposed to use Silicon Photomultipliers and Photomultiplier Tubes together. The Photomultiplier Tube signals serve as a trigger to mitigate the dark count rate, thereby preventing undue saturation of the available bandwidth. This paper presents an investigation into a fast and resource-efficient method for filtering the Silicon Photomultiplier dark count rate. A low-resource and fast coincident filter has been developed, which removes the Silicon Photomultiplier dark count rate by using as a trigger the Photomultiplier Tube input signals. The architecture of the coincidence filter, together with the first results obtained, which validate the effectiveness of this method, is presented. |
Address |
[Real, Diego; Calvo, David; Zornoza, Juan de Dios; Manzaneda, Mario; Gozzini, Rebecca; Albiol, Francisco] CSIC Univ Valencia, IFIC Inst Fis Corpuscular, C Catedrat Jose Beltran 2, Paterna 46980, Spain, Email: real@ific.uv.es; |
Corporate Author |
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Thesis |
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Publisher |
Mdpi |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
|
Notes |
WOS:001201226600001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
6063 |
Permanent link to this record |
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Author |
Albiol, F.; Corbi, A.; Albiol, A. |
Title |
Evaluation of modern camera calibration techniques for conventional diagnostic X-ray imaging settings |
Type |
Journal Article |
Year |
2017 |
Publication |
Radiological Physics and Technology |
Abbreviated Journal |
Radiol. Phys. Technol. |
Volume |
10 |
Issue |
1 |
Pages |
68-81 |
Keywords |
Conventional X-ray camera calibration; Detector resolution; Intrinsic and extrinsic parameters; Zhang's method; Direct linear transform; Tsai's approach |
Abstract |
We explore three different alternatives for obtaining intrinsic and extrinsic parameters in conventional diagnostic X-ray frameworks: the direct linear transform (DLT), the Zhang method, and the Tsai approach. We analyze and describe the computational, operational, and mathematical background differences for these algorithms when they are applied to ordinary radiograph acquisition. For our study, we developed an initial 3D calibration frame with tin cross-shaped fiducials at specific locations. The three studied methods enable the derivation of projection matrices from 3D to 2D point correlations. We propose a set of metrics to compare the efficiency of each technique. One of these metrics consists of the calculation of the detector pixel density, which can be also included as part of the quality control sequence in general X-ray settings. The results show a clear superiority of the DLT approach, both in accuracy and operational suitability. We paid special attention to the Zhang calibration method. Although this technique has been extensively implemented in the field of computer vision, it has rarely been tested in depth in common radiograph production scenarios. Zhang's approach can operate on much simpler and more affordable 2D calibration frames, which were also tested in our research. We experimentally confirm that even three or four plane-image correspondences achieve accurate focal lengths. |
Address |
[Albiol, Francisco; Corbi, Alberto] Univ Valencia, CSIC, Inst Fis Corpuscular, Valencia, Spain, Email: alberto.corbi@ific.uv.es |
Corporate Author |
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Thesis |
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Publisher |
Springer Japan Kk |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1865-0333 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000405867100009 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
3238 |
Permanent link to this record |
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Author |
Schaffter, T. et al; Albiol, F.; Caballero, L. |
Title |
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms |
Type |
Journal Article |
Year |
2020 |
Publication |
JAMA Network Open |
Abbreviated Journal |
JAMA Netw. Open |
Volume |
3 |
Issue |
3 |
Pages |
e200265 - 15pp |
Keywords |
|
Abstract |
Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results Overall, 144231 screening mammograms from 85580 US women (952 cancer positive <= 12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166578 examinations from 68008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation. Question How do deep learning algorithms perform compared with radiologists in screening mammography interpretation? Findings In this diagnostic accuracy study using 144231 screening mammograms from 85580 women from the United States and 166578 screening mammograms from 68008 women from Sweden, no single artificial intelligence algorithm outperformed US community radiologist benchmarks; including clinical data and prior mammograms did not improve artificial intelligence performance. However, combining best-performing artificial intelligence algorithms with single-radiologist assessment demonstrated increased specificity. Meaning Integrating artificial intelligence to mammography interpretation in single-radiologist settings could yield significant performance improvements, with the potential to reduce health care system expenditures and address resource scarcity experienced in population-based screening programs. This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms. |
Address |
[Schaffter, Thomas; Hoff, Bruce; Yu, Thomas; Neto, Elias Chaibub; Friend, Stephen; Guinney, Justin] Sage Bionetworks, Computat Oncol, Seattle, WA USA, Email: gustavo@us.ibm.com |
Corporate Author |
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Thesis |
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Publisher |
Amer Medical Assoc |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2574-3805 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000519249800002 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4683 |
Permanent link to this record |
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Author |
Albiol, F.; Corbi, A.; Albiol, A. |
Title |
Densitometric Radiographic Imaging With Contour Sensors |
Type |
Journal Article |
Year |
2019 |
Publication |
IEEE Access |
Abbreviated Journal |
IEEE Access |
Volume |
7 |
Issue |
|
Pages |
18902-18914 |
Keywords |
Conventional X-ray imaging; contour data; densitometric images; dynamic range; depth information |
Abstract |
We present the technical/physical foundations of a new imaging technique that combines ordinary radiographic information (generated by conventional X-ray settings) with the patient's volume to derive densitometric images. Traditionally, these images provide quantitative information about tissues densities. In our approach, they graphically enhance either soft or bony regions. After measuring the patient's volume with contour recognition devices, the physical traversed lengths within it (as the Roentgen beam intersects the patient) are calculated and pixel-wise associated with the original radiograph (X). In order to derive this map of lengths (L), the camera equations of the X-ray system and the contour sensor are determined. The patient's surface is also translated to the point-of-view of the X-ray beam and all its entrance/exit points are sought with the help of ray-casting methods. The derived L is applied to X as a physical operation (subtraction), obtaining soft tissue-(D-S) or bone-enhanced (D'(B)) figures. In the D-S type, the contained graphical information can be linearly mapped to the average electronic density (traversed by the X-ray beam). This feature represents an interesting proof-of-concept of associating density data to radiographs, but most important, their intensity histogram is objectively compressed, i.e., the dynamic range is more shrunk (compared against the corresponding X). This leads to other advantages: improvement in the visibility of border/edge areas (high gradient), extended manual window level/width manipulations during screening, and immediate correction of underexposed X instances. In the D-B' type, high-density elements are highlighted and easier to discern. All these results can be achieved with low-energy beam exposures, saving costs and dose. Future work will deepen this clinical side of our research. In contrast with other image-based modifiers, the proposed method is grounded on the measurement of a physical entity: the span of the X-ray beam within a body while undertaking a radiographic examination. |
Address |
[Albiol, Francisco; Corbi, Alberto] CSIC, Inst Fis Corpuscular, Paterna 46980, Spain, Email: kiko@ific.uv.es |
Corporate Author |
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Thesis |
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Publisher |
Ieee-Inst Electrical Electronics Engineers Inc |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2169-3536 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000459591800001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
3920 |
Permanent link to this record |
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Author |
Agramunt, J. et al; Tain, J.L.; Albiol, F.; Algora, A.; Domingo-Pardo, C.; Jordan, M. D.; Rubio, B.; Tarifeño-Saldivia, A.; Valencia, E. |
Title |
Characterization of a neutron-beta counting system with beta-delayed neutron emitters |
Type |
Journal Article |
Year |
2016 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
Volume |
807 |
Issue |
|
Pages |
69-78 |
Keywords |
Beta-delayed neutron emission probability; Neutron and beta counters; Self-triggered digital data acquisition system; Geant4 simulations |
Abstract |
A new detection system for the measurement of beta-delayed neutron emission probabilities has been characterized using fission products with well known beta-delayed neutron emission properties. The setup consists of BELEN-20, a 4 pi-neutron counter with twenty He-3 proportional tubes arranged inside a large polyethylene neutron moderator, a thin Si detector for beta counting and a self-triggering digital data acquisition system. The use of delayed-neutron precursors with different neutron emission windows allowed the study of the effect of energy dependency on neutron, beta and beta-neutron rates. The observed effect is well reproduced by Monte Carlo simulations. The impact of this dependency on the accuracy of neutron emission probabilities is discussed. A new accurate value of the neutron emission probability for the important delayed-neutron precursor I-137 was obtained, P-n = 7.76(14)%. |
Address |
[Agramunt, J.; Tain, J. L.; Albiol, E.; Algora, A.; Domingo-Pardo, C.; Jordan, M. D.; Rubio, B.; Tarifeno-Saldivia, A.; Valencia, E.] Univ Valencia, CSIC, Inst Fis Corpuscular, E-46071 Valencia, Spain, Email: Tain@ific.uv.es |
Corporate Author |
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Thesis |
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Publisher |
Elsevier Science Bv |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0168-9002 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000365596200010 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
2481 |
Permanent link to this record |
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Author |
Albiol, A.; Corbi, A.; Albiol, F. |
Title |
Automatic intensity windowing of mammographic images based on a perceptual metric |
Type |
Journal Article |
Year |
2017 |
Publication |
Medical Physics |
Abbreviated Journal |
Med. Phys. |
Volume |
44 |
Issue |
4 |
Pages |
1369-1378 |
Keywords |
contrast stretching; Gabor filtering; human visual system; mammogram; mutual information; window level/width |
Abstract |
Purpose: Initial auto-adjustment of the window level WL and width WW applied to mammographic images. The proposed intensity windowing (IW) method is based on the maximization of the mutual information (MI) between a perceptual decomposition of the original 12-bit sources and their screen displayed 8-bit version. Besides zoom, color inversion and panning operations, IW is the most commonly performed task in daily screening and has a direct impact on diagnosis and the time involved in the process. Methods: The authors present a human visual system and perception-based algorithm named GRAIL (Gabor-relying adjustment of image levels). GRAIL initially measures a mammogram's quality based on the MI between the original instance and its Gabor-filtered derivations. From this point on, the algorithm performs an automatic intensity windowing process that outputs the WL/WW that best displays each mammogram for screening. GRAIL starts with the default, high contrast, wide dynamic range 12-bit data, and then maximizes the graphical information presented in ordinary 8-bit displays. Tests have been carried out with several mammogram databases. They comprise correlations and an ANOVA analysis with the manual IW levels established by a group of radiologists. A complete MATLAB implementation of GRAIL is available at . Results: Auto-leveled images show superior quality both perceptually and objectively compared to their full intensity range and compared to the application of other common methods like global contrast stretching (GCS). The correlations between the human determined intensity values and the ones estimated by our method surpass that of GCS. The ANOVA analysis with the upper intensity thresholds also reveals a similar outcome. GRAIL has also proven to specially perform better with images that contain micro-calcifications and/or foreign X-ray-opaque elements and with healthy BI-RADS A-type mammograms. It can also speed up the initial screening time by a mean of 4.5 s per image. Conclusions: A novel methodology is introduced that enables a quality-driven balancing of the WL/WW of mammographic images. This correction seeks the representation that maximizes the amount of graphical information contained in each image. The presented technique can contribute to the diagnosis and the overall efficiency of the breast screening session by suggesting, at the beginning, an optimal and customized windowing setting for each mammogram. |
Address |
[Albiol, Alberto] Univ Politecn Valencia, iTeam Res Inst, Valencia, Spain, Email: alberto.corbi@ific.uv.es |
Corporate Author |
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Thesis |
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Publisher |
Wiley |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0094-2405 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000400572700016 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
3122 |
Permanent link to this record |
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Author |
Tortajada, S.; Albiol, F.; Caballero, L.; Albiol, A.; Leganes-Nieto, J.L. |
Title |
A portable geometry-independent tomographic system for gamma-ray, a next generation of nuclear waste characterization |
Type |
Journal Article |
Year |
2023 |
Publication |
Scientific Reports |
Abbreviated Journal |
Sci Rep |
Volume |
13 |
Issue |
1 |
Pages |
12284 - 10pp |
Keywords |
|
Abstract |
One of the main activities of the nuclear industry is the characterisation of radioactive waste based on the detection of gamma radiation. Large volumes of radioactive waste are classified according to their average activity, but often the radioactivity exceeds the maximum allowed by regulators in specific parts of the bulk. In addition, the detection of the radiation is currently based on static detection systems where the geometry of the bulk is fixed and well known. Furthermore, these systems are not portable and depend on the transport of waste to the places where the detection systems are located. However, there are situations where the geometry varies and where moving waste is complex. This is especially true in compromised situations.We present a new model for nuclear waste management based on a portable and geometry-independent tomographic system for three-dimensional image reconstruction for gamma radiation detection. The system relies on a combination of a gamma radiation camera and a visible camera that allows to visualise radioactivity using augmented reality and artificial computer vision techniques. This novel tomographic system has the potential to be a disruptive innovation in the nuclear industry for nuclear waste management. |
Address |
[Tortajada, Salvador; Albiol, Francisco; Caballero, Luis] Univ Valencia, CSIC, Inst Fis Corpuscular, E-46980 Paterna Valencia, Spain, Email: s.tortajada@ific.uv.es |
Corporate Author |
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Thesis |
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Publisher |
Nature Portfolio |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2045-2322 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:001041587900052 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
no |
Call Number |
IFIC @ pastor @ |
Serial |
5612 |
Permanent link to this record |