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Showing result 1 - 5 of 27 essays matching the above criteria.
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1. Simulating metal ct artefacts for ground truth generation in deep learning.
University essay from Lunds universitet/Avdelningen för Biomedicinsk teknikAbstract : CT scanning stands as one of the most employed imaging techniques used in clinical field. In the presence of metal implants in the field of view (FOV), distortions and noise appear on the 3D image leading to inaccurate bone segmentation, often required for surgery planning or implant design. READ MORE
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2. Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction
University essay from KTH/Matematisk statistikAbstract : Cone Beam Computed Tomography is a technology to visualize the 3D interior anatomy of a patient. It is important for image-guided radiation therapy in cancer treatment. During a scan, iterative methods are often used for the image reconstruction step. READ MORE
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3. Identification of Fibers in Micro-CT Images of Paperboard Using Deep Learning
University essay from Lunds universitet/Hållfasthetslära; Lunds universitet/Institutionen för byggvetenskaperAbstract : This master thesis project explores the possibility of using deep learning to segment individual fibers in three-dimensional tomography images of paperboard fiber networks. We test a method which has previously been used to segment fibers in images of glass fiber reinforced polymers. READ MORE
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4. Correlation between Surface and Tumour Motion in Lung Cancer - including Deep Learning Perspectives
University essay from Lunds universitet/SjukhusfysikerutbildningenAbstract : Purpose: The purpose of this master thesis was to retrospectively investigate correlation between surface and tumour motion in lung cancer patients, alongside deep learning applications of the results. Additional correlations such as age, tumour volume and anatomical placement of the tumour were also investigated. READ MORE
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5. Automatic Detection of Structural Deformations in Batteries from Imaging data using Machine Learning : Exploring the potential of different approaches for efficient structural deformation detection
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The increasing occurrence of structural deformations in the electrodes of the jelly roll has raised quality concerns during battery manufacturing, emphasizing the need to detect them automatically with the advanced techniques. This thesis aims to explore and provide two models based on traditional computer vision (CV) and deep neural network (DNN) techniques using computed tomography (CT) scan images of jelly rolls to ensure that the product is of high quality. READ MORE