Sökning: "UNet"
Visar resultat 1 - 5 av 28 uppsatser innehållade ordet UNet.
1. Virtual H&E Staining Using PLS Microscopy and Neural Networks
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : 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
2. Physiology-Guided Machine Learning for Improved Reliability of Non-Invasive Assessment of Pulmonary Hypertension
Master-uppsats, Linköpings universitet/Avdelningen för medicinsk teknikSammanfattning : Diagnosing pulmonary hypertension (PH) with right heart catheterization (RHC) is associated with a risk for complications and high expenses, leading to late diagnoses [1]. Transthoracic echocardiography can be used to assess non-invasive indicators for PH such as right ventricular systolic pressure (RVSP), which can be estimated by combining the peak tricuspid regurgitation velocity (TRV) with the estimated right arterial pressure (RAP). LÄS MER
3. Deep Learning for the prediction of RASER-MRI profiles
Master-uppsats, Linköpings universitet/Medie- och InformationsteknikSammanfattning : Magnetic resonance imaging (MRI) is a critical diagnostic tool in medical practice, enabling non-invasive visualization of anatomy and physiological processes. Nonetheless, MRI has inherent spatial resolution limitations, which may limit its diagnostic capabilities. LÄS MER
4. 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
5. Evaluation of Computer Tomography based Cancer Diagnostics with the help of 3D Printed Phantoms and Deep Learning
Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)Sammanfattning : Computed x-ray tomography is one of the most common medical imaging modalities andas such ways of improving the images are of high relevance. Applying deep learningmethods to denoise CT images has been of particular interest in recent years. LÄS MER