Sökning: "Image segmentation"

Visar resultat 6 - 10 av 431 uppsatser innehållade orden Image segmentation.

  1. 6. Network Orientation and Segmentation Refinement Using Machine Learning

    Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknik

    Författare :Michael Nilsson; Jonatan Kentson; [2023]
    Nyckelord :deep learning; semantic segmentation; orientation learning; road networks; retina networks;

    Sammanfattning : Network mapping is used to extract the coordinates of a network's components in an image. Furthermore, machine learning algorithms have demonstrated their efficacy in advancing the field of network mapping across various domains, including mapping of road networks and blood vessel networks. LÄS MER

  3. 7. Analyzing the Influence of Synthetic andAugmented Data on Segmentation Model

    Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Alex Peschel; [2023]
    Nyckelord :Artificial Intelligence; Microorganisms; Segmentation; Synthesizing; Augmentation;

    Sammanfattning : The field of Artificial Intelligence (AI) has experienced unprecedented growth in recent years, thanks to the numerous applications related to speech recognition, natural language processing, and computer vision. However, one of the challenges facing AI is the requirement for large amounts of energy, time, and data to be effective and accurate. LÄS MER

  4. 8. Image Segmentation and Object Identification in Cancer Tissue Slides from Fluorescence Microscopy

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen Vi3

    Författare :Sebastian Eriksson; Fredrik Forsberg; [2023]
    Nyckelord :image analysis; cancer research; fluorescent microscopy; image segmentation; bildanalys; cancerforskning; fluorescensmikroskopi; bildsegmentering;

    Sammanfattning : In cancer research, there is a need to make accurate spatial measurements in multi-layered fluorescence microscopy images. Researchers would like to measure distances in and between biological objects such as nerves and tumours, to investigate questions which includes if nerve distribution in and around tumours can have a prognostic value in cancer diagnostics. LÄS MER

  5. 9. Domain Adaptation for Multi-Contrast Image Segmentation in Cardiac Magnetic Resonance Imaging

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Thomas Proudhon; [2023]
    Nyckelord :Cardiac Magnetic Resonance Imaging; Deep Learning; Domain Adaptation; Unsupervised Segmentation; Image-to-image Translation;

    Sammanfattning : Accurate segmentation of the ventricles and myocardium on Cardiac Magnetic Resonance (CMR) images is crucial to assess the functioning of the heart or to diagnose patients suffering from myocardial infarction. However, the domain shift existing between the multiple sequences of CMR data prevents a deep learning model trained on a specific contrast to be used on a different sequence. LÄS MER

  7. 10. 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