Sökning: "Medical Imaging"

Visar resultat 1 - 5 av 272 uppsatser innehållade orden Medical Imaging.

1. 1. Robustness Analysis of Perfusion Parameter Calculations

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

   Författare :Alicia Palmér; [2024]
   Nyckelord :Perfusion; Medical image analysis; Dynamic Contrast Enhanced Magnetic Resonance Imaging; Tofts model; Functional imaging; Optimization; T1 map; Perfusion; Medicinsk bildanalys; Dynamisk kontrastförstärkt magnetisk resonanstomografibildtagning; Tofts-modell; Funktionell bildbehandling; Optimering; T1 karta;

   Sammanfattning : Cancer is one of the most common causes of death worldwide. When given optimal treatment, however, the risk of severe illness may greatly be reduced. Determining optimal treatment in turn requires evaluation of disease progression and response to potential, previous treatment. 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. Virtual H&E Staining Using PLS Microscopy and Neural Networks

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Sally Vizins; Hanna Råhnängen; [2024]
   Nyckelord :Deep learning; Virtual staining; Skin tissue; Hematoxylin Eosin; H E; Pathology; Carcinoma; Point light source illumination; Neural Networks; GANs; Generative adversarial networks; CNNs; Convolutional neural networks; Relativistic generative adversarial network; Unet; Digital microscopy; Attention-Unet; Dense-Unet; Mathematics and Statistics;

   Sammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER

5. 4. 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

7. 5. Anatomical segmentation of the human brain: comparative assessment of two automatic methods

   Master-uppsats,

   Författare :Carl von Dorrien; [2023-08-22]
   Nyckelord :Medical physics; MAPER; FreeSurfer; FastSurfer; Automatic brain segmentation; MRI; Deep Neural Network; Brain;

   Sammanfattning : Magnetic Resonance Imaging (MRI) is a robust and versatile imaging modality and an integral component of a lot of studies, especially when performing quantitative analysis. MRI is the preferred method of imaging the brain because of its excellent soft tissue contrast. LÄS MER