WITHDRAWN: Performance analysis of Glioma brain tumor detection and segmentation using image registration technique

Selvapandian, A.; Athilingam, R.; Sivakumar, P.

doi:10.1016/j.matpr.2020.09.601

Cited by 1 publication

(1 citation statement)

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“…Image registration is a classical method 48 that continues in the state of the art, used for diverse applications based on image processing approaches, 49 some examples are as follows: image processing for body analysis and medical diagnosis, 50 images background removal, 51 2D and 3D model reconstruction, 52 and moving object detection and tracking, 53 as in the proposed work. Every time, two or more images from different sources, times, or viewpoints require to be compared, image registration methods can be applied.…”

Section: Computational Models As Blcs For Vbi Assessmentmentioning

confidence: 99%

A structural health monitoring method proposal based on optical scanning and computational models

Flores-Fuentes

Alba-Corpus

Sergiyenko

et al. 2022

International Journal of Distributed Sensor Networks

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This article proposes a method for continuous bridge displacement monitoring combining the dynamic triangulation scanning and load estimation by vehicle image recognition. The vehicle–bridge interaction is a non-stationary dynamic process parameter of high relevance to understanding the static instability behavior of bridges. The knowledge of the load on a bridge in the specific time when its structural spatial coordinates are measured allows correlating the bridge displacement with the effect of vehicle–bridge interaction. The evaluation of such correlation is mandatory in order to verify if the observed bridge displacement is due to the nature of its operation or due to it is presenting structural damage. The proposed method is continuous structural health monitoring method, based on the combination of three approaches evaluated at laboratory environment: (1) a three-dimensional optical scanning system for displacement measurement, (2) a load measurement system for vehicle–bridge interaction assessment, and (3) a two-measurement systems data correlation; to be implemented in bridges at a real environment to collect their historical behavior. Overall, for each approach, the measurement systems’ principles, the laboratory experimental methodology followed, and results obtained are presented.

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