University of Ljubljana

Fusing optical coherence tomography and photodiodes for diagnosis of weld features during remote laser welding of copper-to-aluminum

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This study has been designed to investigate whether variations in the features of laser weldments can be isolated and diagnosed by fusing photodiodes and optical coherence tomography (OCT). Two manufacturing scenarios (variation in laser power and focal offset) have been considered during remote laser welding of 0.2 mm thick Cu foils on 2 mm thick Al 1050 plates with an adjustable ring mode laser integrated with a 1D oscillation head. The process was monitored by measuring weld penetration depth with OCT and by process emissions (plasma and back-reflection) via photodiodes. The acquisition frequency of all signals was 40 kHz. Strong correlations (r > 0.75) were shown between plasma, back-reflection, and OCT signals and measured depth and width of the weld. Weak correlations (r < 0.5) between voids, cracks, and sensor signals were observed. Although plasma is the predominant signal that carries most of the information about the process, and the OCT allows direct measurement of ...

A vision transformer architecture for the automated segmentation of retinal lesions in spectral domain optical coherence tomography images

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Neovascular age-related macular degeneration (nAMD) is one of the major causes of irreversible blindness and is characterized by accumulations of different lesions inside the retina. AMD biomarkers enable experts to grade the AMD and could be used for therapy prognosis and individualized treatment decisions. In particular, intra-retinal fluid (IRF), sub-retinal fluid (SRF), and pigment epithelium detachment (PED) are prominent biomarkers for grading neovascular AMD. Spectral-domain optical coherence tomography (SD-OCT) revolutionized nAMD early diagnosis by providing cross-sectional images of the retina. Automatic segmentation and quantification of IRF, SRF, and PED in SD-OCT images can be extremely useful for clinical decision-making. Despite the excellent performance of convolutional neural network (CNN)-based methods, the task still presents some challenges due to relevant variations in the location, size, shape, and texture of the lesions. This work adopts a transformer-based me...

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