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Visar resultat 1 - 5 av 81 uppsatser som matchar ovanstående sökkriterier.

  1. 1. 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

  3. 2. Real-time Autofocus Algorithm in Laser Speckle Contrast Imaging

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

    Författare :Giovanni Russo; [2023]
    Nyckelord :Laser speckle contrast imaging; Autofocus; Blind image sharpness assessment; Speckle noise; Perimed’s Perfusion Speckle Imager;

    Sammanfattning : Microcirculation is defined as the blood flow in the smallest blood vessels. Laser speckle contrast imaging (LSCI) is a full field imaging technique that provides instantaneous 2-D perfusion maps of illuminated tissues based on speckle contrast. LÄS MER

  4. 3. Multiclass Brain Tumour Tissue Classification on Histopathology Images Using Vision Transformers

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Christoforos Spyretos; [2023]
    Nyckelord :medical imaging; deep learning; classification; CNN; Vision Transformer; glioblastoma; GBM; IvyGAP; brain tumour; histopathology; digital pathology; histology;

    Sammanfattning : Histopathology refers to inspecting and analysing tissue samples under a microscope to identify and examine signs of diseases. The manual investigation procedure of histology slides by pathologists is time-consuming and susceptible to misconceptions. LÄS MER

  5. 4. Deep Learning Based Focus lnterpolation for Whole Slide Images

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Davis Nicmanis; [2022]
    Nyckelord :;

    Sammanfattning : Whole slide imaging is a crucial component of digital pathology, which emulates conventional microscopy by scanning the entire microscope slide. It results in a large digital image that can be examined by a cytopathologist or used in further computer-assisted image analysis. LÄS MER

  7. 5. Automated HER2 Scoring of Breast Cancer Tissue using Upconverting Nanoparticle Images

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Adam Belfrage; Alexander Wik; [2022]
    Nyckelord :HER2-scoring; image analysis; interpretability; digital pathology; computer aided pathology; whole slide imaging; ASCO-guidelines; singular value decomposition; shape models; Bayesian classification; Biology and Life Sciences; Medicine and Health Sciences; Technology and Engineering; Mathematics and Statistics;

    Sammanfattning : Computer aided pathology is becoming more and more of a requirement within pathology due to increased demand of individualised treatments and personalised medicine. Because of the advance of digital pathology in recent years, where a high resolution camera acquire images of microscope slides, pathologists can now assess tissue samples in digital images. LÄS MER