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Author  |
Albiol, A.; Albiol, F.; Paredes, R.; Plasencia-Martinez, J.M.; Blanco Barrio, A.; Garcia Santos, J.M.; Tortajada, S.; Gonzalez Montano, V.M.; Rodriguez Godoy, C.E.; Fernandez Gomez, S.; Oliver-Garcia, E.; de la Iglesia Vaya, M.; Marquez Perez, F.L.; Rayo Madrid, J.I. |
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Title |
A comparison of Covid-19 early detection between convolutional neural networks and radiologists |
Type |
Journal Article |
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Year |
2022 |
Publication |
Insights into Imaging |
Abbreviated Journal |
Insights Imaging |
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Volume |
13 |
Issue |
1 |
Pages |
122 - 12pp |
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Keywords |
Deep learning; Covid-19; Radiology |
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Abstract |
Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19. |
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Address |
[Albiol, Alberto] Univ Politecn Valencia, iTeam Inst, ETSI Telecomunicac, Camino Vera S-N, Valencia 46022, Spain, Email: alalbiol@iteam.upv.es |
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Springer |
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English |
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ISSN |
1869-4101 |
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Notes |
WOS:000832727200003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5302 |
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Author |
Albiol, A.; Corbi, A.; Albiol, F. |
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Title |
Automatic intensity windowing of mammographic images based on a perceptual metric |
Type |
Journal Article |
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Year |
2017 |
Publication |
Medical Physics |
Abbreviated Journal |
Med. Phys. |
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Volume |
44 |
Issue |
4 |
Pages |
1369-1378 |
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Keywords |
contrast stretching; Gabor filtering; human visual system; mammogram; mutual information; window level/width |
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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. |
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Address |
[Albiol, Alberto] Univ Politecn Valencia, iTeam Res Inst, Valencia, Spain, Email: alberto.corbi@ific.uv.es |
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Publisher |
Wiley |
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English |
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Edition |
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ISSN |
0094-2405 |
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Conference |
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Notes |
WOS:000400572700016 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3122 |
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Author |
Albiol, F.; Corbi, A.; Albiol, A. |
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Title |
Densitometric Radiographic Imaging With Contour Sensors |
Type |
Journal Article |
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Year |
2019 |
Publication |
IEEE Access |
Abbreviated Journal |
IEEE Access |
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Volume |
7 |
Issue |
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Pages |
18902-18914 |
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Keywords |
Conventional X-ray imaging; contour data; densitometric images; dynamic range; depth information |
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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. |
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Address |
[Albiol, Francisco; Corbi, Alberto] CSIC, Inst Fis Corpuscular, Paterna 46980, Spain, Email: kiko@ific.uv.es |
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Publisher |
Ieee-Inst Electrical Electronics Engineers Inc |
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Language |
English |
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Edition |
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ISSN |
2169-3536 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000459591800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3920 |
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Author |
Albiol, F.; Corbi, A.; Albiol, A. |
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Title |
3D measurements in conventional X-ray imaging with RGB-D sensors |
Type |
Journal Article |
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Year |
2017 |
Publication |
Medical Engineering & Physics |
Abbreviated Journal |
Med. Eng. Phys. |
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Volume |
42 |
Issue |
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Pages |
73-79 |
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Keywords |
X-ray; Depth cameras; Epipolar geometry; 3D reconstruction; Movement tracking; Dense surface mapping |
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Abstract |
A method for deriving 3D internal information in conventional X-ray settings is presented. It is based on the combination of a pair of radiographs from a patient and it avoids the use of X-ray-opaque fiducials and external reference structures. To achieve this goal, we augment an ordinary X-ray device with a consumer RGB-D camera. The patient' s rotation around the craniocaudal axis is tracked relative to this camera thanks to the depth information provided and the application of a modern surface-mapping algorithm. The measured spatial information is then translated to the reference frame of the X-ray imaging system. By using the intrinsic parameters of the diagnostic equipment, epipolar geometry, and X-ray images of the patient at different angles, 3D internal positions can be obtained. Both the RGB-D and Xray instruments are first geometrically calibrated to find their joint spatial transformation. The proposed method is applied to three rotating phantoms. The first two consist of an anthropomorphic head and a torso, which are filled with spherical lead bearings at precise locations. The third one is made of simple foam and has metal needles of several known lengths embedded in it. The results show that it is possible to resolve anatomical positions and lengths with a millimetric level of precision. With the proposed approach, internal 3D reconstructed coordinates and distances can be provided to the physician. It also contributes to reducing the invasiveness of ordinary X-ray environments and can replace other types of clinical explorations that are mainly aimed at measuring or geometrically relating elements that are present inside the patient's body. |
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Address |
[Albiol, Francisco; Corbi, Alberto] Univ Valencia, CSIC, Inst Fis Corpuscular, E-46003 Valencia, Spain, Email: alberto.corbi@ific.uv.es |
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Publisher |
Elsevier Sci Ltd |
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English |
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ISSN |
1350-4533 |
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Conference |
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Notes |
WOS:000398007100008 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3043 |
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Author |
Albiol, F.; Corbi, A.; Albiol, A. |
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Title |
Evaluation of modern camera calibration techniques for conventional diagnostic X-ray imaging settings |
Type |
Journal Article |
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Year |
2017 |
Publication |
Radiological Physics and Technology |
Abbreviated Journal |
Radiol. Phys. Technol. |
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Volume |
10 |
Issue |
1 |
Pages |
68-81 |
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Keywords |
Conventional X-ray camera calibration; Detector resolution; Intrinsic and extrinsic parameters; Zhang's method; Direct linear transform; Tsai's approach |
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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. |
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Address |
[Albiol, Francisco; Corbi, Alberto] Univ Valencia, CSIC, Inst Fis Corpuscular, Valencia, Spain, Email: alberto.corbi@ific.uv.es |
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Publisher |
Springer Japan Kk |
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English |
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Abbreviated Series Title |
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ISSN |
1865-0333 |
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Notes |
WOS:000405867100009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3238 |
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Author |
Albiol, F.; Corbi, A.; Albiol, A. |
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Title |
Geometrical Calibration of X-Ray Imaging With RGB Cameras for 3D Reconstruction |
Type |
Journal Article |
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Year |
2016 |
Publication |
IEEE Transactions on Medical Imaging |
Abbreviated Journal |
IEEE Trans. Med. Imaging |
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Volume |
35 |
Issue |
8 |
Pages |
1952-1961 |
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Keywords |
3D reconstruction; camera system; geometric calibration; visible fiducials; X-ray imaging |
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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. |
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Address |
[Albiol, Francisco; Corbi, Alberto] Univ Valencia, Consejo Super Invest Cient, Inst Fis Corpuscular IFIC, Paterna 46980, Spain, Email: kiko@ific.uv.es; |
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Publisher |
Ieee-Inst Electrical Electronics Engineers Inc |
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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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ISSN |
0278-0062 |
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Notes |
WOS:000381436000016 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
2781 |
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Author |
Tortajada, S.; Albiol, F.; Caballero, L.; Albiol, A.; Leganes-Nieto, J.L. |
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Title |
A portable geometry-independent tomographic system for gamma-ray, a next generation of nuclear waste characterization |
Type |
Journal Article |
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Year |
2023 |
Publication |
Scientific Reports |
Abbreviated Journal |
Sci Rep |
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Volume |
13 |
Issue |
1 |
Pages |
12284 - 10pp |
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Keywords |
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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. |
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Address |
[Tortajada, Salvador; Albiol, Francisco; Caballero, Luis] Univ Valencia, CSIC, Inst Fis Corpuscular, E-46980 Paterna Valencia, Spain, Email: s.tortajada@ific.uv.es |
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Publisher |
Nature Portfolio |
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English |
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ISSN |
2045-2322 |
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Notes |
WOS:001041587900052 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5612 |
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