|
|
The use of deep neural networks for the evaluation of metallographic cross-sections
Semančík, Adam ; Mendřický, Radomír (oponent) ; Hurník, Jakub (vedoucí práce)
This thesis explores the application of deep neural networks to improve the evaluation of metallographic cross-sections in materials produced through powder bed fusion. It focuses on two advanced image processing techniques: semantic segmentation and image super-resolution. A U-Net architecture was used for semantic segmentation to classify defects such as lack of fusion porosity and gas porosity. Additionally, an SRGAN (Super-Resolution Generative Adversarial Network) model was utilized to upscale image resolution, potentially enhancing segmentation accuracy. The research assesses whether a model trained on AlSi10Mg can generalize to Cu99 and Ti6Al4V and evaluates the influence of super-resolution on segmentation performance. Results showed that while the segmentation model performed well on AlSi10Mg, generalization to other materials required more diverse training data. Due to computational limitations, the combined effect of super-resolution and segmentation remains inconclusive, suggesting further research with enhanced computational resources.
|
|
|
Coherence gated holographic microscopy
Ďuriš, Miroslav ; Tyc,, Tomáš (oponent) ; Baránek,, Michal (oponent) ; Chmelík, Radim (vedoucí práce)
Biomedical and metasurface researchers repeatedly reach for quantitative phase imaging (QPI) as their primary imaging technique due to its high-throughput, label-free, quantitative nature. Therefore, QPI has quickly established its role in identifying rare events and screening in biomedicine or automated image data analysis using artificial intelligence. These and many other applications share the requirement for extensive high-quality datasets, which is challenging to meet due to obstacles specific to each application. This thesis tackles the principal problems of optical imaging, mainly in biomedical research. The research aimed to study and develop new imaging methods by extending the capabilities of the coherence-controlled holographic microscope. In the thesis, we tackled three principal areas of biomedical imaging: turbid media imaging, super-resolution QPI, and 3D refractive index reconstruction. To achieve such ambitious results, we have utilized the so-called coherence-gating effect, typically exploited for imaging through disordered media by least-scattered (ballistic) light. To tackle turbid media imaging, we counterintuitively use the coherence gate for imaging by the non-ballistic light, enabling us to retrieve information missing in the ballistic image. A combination of images for different coherence gate positions allow us to synthesize an image of quality superior to ballistic light approaches, which we experimentally demonstrate on QPI through thick biological tissue. Two approaches to super-resolution QPI were explored in the thesis. First is the synthetic aperture approach, for which we again exploit the coherence-gating properties of the partially coherent light combined with the oblique illumination provided by the diffraction on a simple hexagonal phase grating placed near the specimen. We synthesize synthetic aperture QPI with significantly increased spatial frequency bandwidth from sequentially acquired images formed by the coherence-gated light scattered into each grating's diffraction order. Second, we developed the coherence gate shaping method allowing real-time super-resolution QPI. We propose an approach based on the fact that our system's point spread function (PSF) is a product of the diffraction-limited spot and the coherence-gating function, which we shape similarly to the superoscillatory hotspot. The product simultaneously produces the PSF with a super-resolution central peak and minimizes sidelobe effects, the common obstacle of superoscillatory imaging. The attenuation of sidelobes and resolution improvement co-occur in the entire field of view. Therefore, we present the first single-shot wide-field super-resolution QPI. For both methods, we achieved a resolution improvement of at least 19\%. Furthermore, we demonstrate the feasibility of the proposed methods by imaging biological specimens with super-resolution. In the thesis, we also address 3D imaging by the coherence-controlled holographic microscope. We developed a method for 3D refractive index distribution reconstruction from a z-stack QPI measurement. The reconstructed refractive index distribution has qualities similar to the outputs of optical diffraction tomography. At the same time, the required number of acquisitions is significantly lower in the case of the proposed method. We demonstrate our approach using simulated as well as experimental data.
|
host ::
RSS.