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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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West, Graeme
University of Strathclyde
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (6/6 displayed)
- 2024CNN-based automated approach to crack-feature detection in steam cycle componentscitations
- 2023Tactile, orientation, and optical sensor fusion for tactile breast image mosaickingcitations
- 2017An expert-systems approach to automatically determining flaw depth within candu pressure tubes
- 2015Automated image stitching for fuel channel inspection of AGR cores
- 2013Automated image stitching for enhanced visual inspections of nuclear power stations
- 2007An automated intelligent analysis system for analysing reactor refuelling events
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article
Tactile, orientation, and optical sensor fusion for tactile breast image mosaicking
Abstract
Breast cancer screening using Tactile Imaging (TI) is an advancing field of low-cost non-invasive medical imaging. Utilizing arrays of capacitive pressure transducers to perform a differential stress measurement of suspicious tissue, TI has been shown to be effective in measuring lesion size and stiffness, and subsequent differentiation of malignant and benign conditions, in repeated clinical studies. In order to further improve the lesion classification accuracy of clinical TI, this paper presents a novel method of mosaicking tactile images to form a large composite tactile map using the vein structure within the breast to spatially register tactile data. This paper demonstrates practical non-rigid tactile image mosaicking, using probe contact force and relative orientation sensor fusion to correct for the tissue deformation during tactile scanning, miniaturized and applied to a pre-clinical TI prototype. Testing of the proposed TI prototype on representative, tissue-mimicking, silicone breast phantoms, with varying baseline elasticity and internal vein structure, yields typical image registration accuracies of 0.33% ± 0.15%. In similar testing, the proposed system measures the background elasticity of the samples with worst case error < 4.5% over the range 9 kPa to 60 kPa, required for accurate lesion characterization. This work will lead into further clinical validation of TI for measurement and classification of in-situ phantom and breast lesions, utilizing the delivered metrics from this work to improve differentiation accuracy.