Sökning: "Tomography"

Visar resultat 11 - 15 av 477 uppsatser innehållade ordet Tomography.

  1. 11. Simulating metal ct artefacts for ground truth generation in deep learning.

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Arthur Barakat; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : 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. LÄS MER

  3. 12. Emphysema Classification via Deep Learning

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Olov Molin; [2023]
    Nyckelord :Deep learning; emphysema; CNN;

    Sammanfattning : 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. LÄS MER

  4. 13. Enhancing Geophysical Applications with Electrical Resistivity Tomography Inversion : Uncovering the mysteries that lies beneath us

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

    Författare :Anton Morian; [2023]
    Nyckelord :Resistivity inversion; Filtering; 3D visualisation;

    Sammanfattning : Geophysical methods have been widely used to investigate the subsurface in various ap-plications, such as mineral exploration, geotechnical and environmental studies. Among these methods, electrical resistivity tomography (ERT) has gained popularity due to its non-invasive and high-resolution capability in mapping subsurface resistivity variations. LÄS MER

  5. 14. Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction

    Master-uppsats, KTH/Matematisk statistik

    Författare :Sabina Syed; Josefin Stenberg; [2023]
    Nyckelord :Adversarial Convex Regularization; Computer Vision; Cone Beam Computed Tomography; Convolutional Neural Networks; Deep Learning; Image Reconstruction; Adversarial Convex Regularization; Bildrekonstruktion; Datorseende; Djupinlärning; Faltningsnätverk; Volymtomografi;

    Sammanfattning : 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. LÄS MER

  7. 15. Self-learning for 3D segmentation of medical images from single and few-slice annotation

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Côme Lassarat; [2023]
    Nyckelord :Self-supervised Learning; Segmentation; Medical images; Självövervakad inlärning; segmentering; medicinska bilder;

    Sammanfattning : 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. LÄS MER