Essays about: "CT image"
Showing result 1 - 5 of 195 essays containing the words CT image.
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1. Few-Shot Learning for Quality Inspection
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : The goal of this project is to find a suitable Few-Shot Learning (FSL) model that can be used in a fault detection system for use in an industrial setting. A dataset of Printed Circuit Board (PCB) images has been created to train different FSL models. READ MORE
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2. 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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3. Emphysema Classification via Deep Learning
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Emphysema is an incurable lung airway disease and a hallmark of Chronic Obstructive Pulmonary Disease (COPD). In recent decades, Computed Tomography (CT) has been used as a powerful tool for the detection and quantification of different diseases, including emphysema. The use of CT comes with a potential risk: ionizing radiation. READ MORE
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4. Self-learning for 3D segmentation of medical images from single and few-slice annotation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Training deep-learning networks to segment a particular region of interest (ROI) in 3D medical acquisitions (also called volumes) usually requires annotating a lot of data upstream because of the predominant fully supervised nature of the existing stateof-the-art models. To alleviate this annotation burden for medical experts and the associated cost, leveraging self-learning models, whose strength lies in their ability to be trained with unlabeled data, is a natural and straightforward approach. READ MORE
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5. 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