Avancerad sökning

Visar resultat 1 - 5 av 174 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Independent validation of a system for real-time localization of the prostate during motion tracking radiotherapy

    Kandidat-uppsats, Lunds universitet/Fysiska institutionen

    Författare :Klara Stefansson; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Intrafractional prostate motion during external beam radiotherapy of prostate tumors has been reported as a limiting factor in accurate treatment delivery. Technology for real-time image-guided radiotherapy has been introduced for tracking and for compensating prostate motion during treatment and could allow for reduced target margins. LÄS MER

  3. 2. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Marisa Wodrich; [2024]
    Nyckelord :Uncertainty quantification; Deep learning; Breast cancer classification; Trustworthy AI; Point-of-care ultrasound; Mathematics and Statistics;

    Sammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER

  4. 3. Exploring adaptation of self-supervised representation learning to histopathology images for liver cancer detection

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

    Författare :Markus Jonsson; [2024]
    Nyckelord :Self-supervised learning; Representation learning; Computer vision;

    Sammanfattning : This thesis explores adapting self-supervised representation learning to visual domains beyond natural scenes, focusing on medical imaging. The research addresses the central question: "How can self-supervised representation learning be specifically adapted for detecting liver cancer in histopathology images?" The study utilizes the PAIP 2019 dataset for liver cancer segmentation and employs a self-supervised approach based on the VICReg method. LÄS MER

  5. 4. Establishment and Characterisation of new Immunoreagents for diagnosis of Ovarian cancer

    H-uppsats,

    Författare :Fanny Carlsson; [2023-04-19]
    Nyckelord :ovarian; cancer; monoclonal; antibodies; biomarkers; CARM1; PARPi; EZH2i;

    Sammanfattning : Ovarian cancer is the most lethal of all gynaecological cancers and it is often diagnosedat an advanced stage due to diffuse and only mild symptoms at early stages.Early detection is crucial to increase survival but high-grade serous ovarian cancer(HGSOC) often presents non-specific symptoms, such as loss of appetite, bloating ofabdomen and tiredness. LÄS MER

  7. 5. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network : Bildklassificering för hjärntumör medhjälp av förtränat konvolutionell tneuralt nätverk

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Ahmad Osman; Bushra Alsabbagh; [2023]
    Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

    Sammanfattning : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells inthe brain. The brain is responsible for regulating the functions of all other organs,hence, any atypical growth of cells in the brain can have severe implications for itsfunctions. The number of global mortality in 2020 led by cancerous brains was estimatedat 251,329. LÄS MER