Sökning: "Cell Segmentation"
Visar resultat 1 - 5 av 27 uppsatser innehållade orden Cell Segmentation.
1. Image-driven simulation of brain tumors using a reaction-diffusion mathematical model
Master-uppsats, Linköpings universitet/Avdelningen för medicinsk teknikSammanfattning : Brain tumors pose a big challenge in the field of neuro-oncology. Gliomas are the largest subgroup. Magnetic resonance imaging is a non-invasive tool for detecting and characterizing these tumors. Mathematical models, such as the reaction-diffusion equation, can be used for understanding the intricate behavior of gliomas. LÄS MER
2. Development of a Complete Minuscule Microscope: Embedding Data Pipeline and Machine Learning Segmentation
Master-uppsats, KTH/Tillämpad fysikSammanfattning : Cell culture is a fundamental procedure in many laboratories and precedes much research performed under the microscope. Despite the significance of this procedural stage, the monitoring of cells throughout growth is impossible due to the absence of equipment and methodological approaches. LÄS MER
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)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
4. Developing Automated Cell Segmentation Models Intended for MERFISH Analysis of the Cardiac Tissue by Deploying Supervised Machine Learning Algorithms
Master-uppsats, KTH/KemiSammanfattning : Följande studie behandlar utvecklandet av automatiserade cellsegmenteringsmodeller med avsikt att identifiera gränser mellan celler i hjärtvävnad. Syftet är att möjliggöra analys av data genererad från multiplexed error-robust in situ hybridization (MERFISH). LÄS MER
5. Cell Identification from Microscopy Images using Deep Learning on Automatically Labeled Data
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : 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