Sökning: "pixel algorithms"

Visar resultat 1 - 5 av 74 uppsatser innehållade orden pixel algorithms.

  1. 1. Indocyanine-green fluorescence imaging to detect anastomotic insufficiency after esophagectomy

    Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Förbränningsfysik

    Författare :Love Kildetoft; [2024]
    Nyckelord :Fluorescence; Imaging; Indocyanine-green; ICG; Esophageal cancer; Physics; Photonics; Image Analysis; Blood Perfusion; Anastomotic leakage; Anastomotic insufficiency; Physics and Astronomy;

    Sammanfattning : This research project is concerned with the development of simulation models and image analysis algorithms, as well as instrumentation for characterizing anastomotic leakages after a patient has undergone surgery for esophageal cancer. Anastomotic leakage is a high-incidence complication after esophagectomy, a surgical procedure for esophageal cancer. LÄS MER

  3. 2. Quality enhancement of time-resolved computed tomography scans with cycleGAN

    Master-uppsats, Lunds universitet/Synkrotronljusfysik; Lunds universitet/Fysiska institutionen

    Författare :Johannes Stubbe; [2023]
    Nyckelord :carbon fibers; carbon fibres; microfibers; tomography; deep learning; cycleGAN; time-resolved tomography; Physics and Astronomy;

    Sammanfattning : Time-resolved x-ray tomography enables us to dynamically and non-destructively study the interior of a specimen. The obtainable temporal resolution is limited by the x-ray flux and the desired spatial resolution. LÄS MER

  4. 3. Segmentation of Neuronal Cells Using Simplistic Methods : A Comparison of the Mean Shift Algorithm and Otsu’s Method

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

    Författare :Alex Gunnarsson; Filip Karlsson; [2023]
    Nyckelord :;

    Sammanfattning : Information regarding specific neuronal characteristics, such as shape and distribution, is essential for quantifying the brain structure and modelling accurate computer simulations. To this end, it is important to perform cell segmentation; to isolate the cells in a given image from the surrounding tissue, so it can be further analysed. LÄS MER

  5. 4. Anomaly Detection with Machine Learning using CLIP in a Video Surveillance Context

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Christoffer Gärdin; [2023]
    Nyckelord :Datorseende; maskininlärning; CLIP; anomalidetektion; videoövervakning;

    Sammanfattning : This thesis explores the application of Contrastive Language-Image Pre-Training (CLIP), a vision-language model, in an automated video surveillance system for anomaly detection. The ability of CLIP to perform zero-shot learning, coupled with its robustness against minor image alterations due to its lack of reliance on pixel-level image analysis, makes it a suitable candidate for this application. LÄS MER

  7. 5. Cell Identification from Microscopy Images using Deep Learning on Automatically Labeled Data

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Fredrik Salomon-Sörensen; [2023]
    Nyckelord :Deep Learning; Cell Identification; Image Segmentation; Nuclei Segmentation; Convolutional Neural Networks; UNet; Image Analysis; Microscopy; Noisy Labels; Phase-Contrast; Automatic Labeling; Technology and Engineering;

    Sammanfattning : In biology, cell counting provides a fundamental metric for live-cell experiments. Unfortunately, most researchers are constrained to using tedious and invasive methods for counting cells. Automatic identification of cells in microscopy images would therefore be a valuable tool for such researchers. LÄS MER