Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Analytical, Diagnostic and Therapeutic Techniques and Equipment (1)
- Artificial Intelligence and Robotics (1)
- Biochemistry, Biophysics, and Structural Biology (1)
- Bioinformatics (1)
- Biotechnology (1)
-
- Cell Biology (1)
- Cell and Developmental Biology (1)
- Computer Sciences (1)
- Congenital, Hereditary, and Neonatal Diseases and Abnormalities (1)
- Disease Modeling (1)
- Diseases (1)
- Nervous System (1)
- Nervous System Diseases (1)
- Neuroscience and Neurobiology (1)
- Other Analytical, Diagnostic and Therapeutic Techniques and Equipment (1)
- Physical Sciences and Mathematics (1)
- Structural Biology (1)
- Keyword
- Publication Type
Articles 1 - 2 of 2
Full-Text Articles in Cells
"Deep Learning For Microscope Image Denoising", Nasreen Buhn, Sriya Adunur, Guy Hagen, Jonathan Ventura
"Deep Learning For Microscope Image Denoising", Nasreen Buhn, Sriya Adunur, Guy Hagen, Jonathan Ventura
College of Engineering Summer Undergraduate Research Program
In order to avoid damaging live cells, optical microscope imaging must be conducted under low-excitation light intensity and/or short exposure times, resulting in low signal-to-noise ratios (SNR). Deep learning methods offer an effective solution for removing microscope noise, utilizing algorithms that are able to reconstruct finer features in low SNR images. This research explores the denoising capability of several deep learning methods based on PSNR and SSIM. Tested methods include traditional approaches (BMED), supervised learning (CARE and Restormer), and unsupervised methods (Noise2Fast, N2V, SSD-Unsupervised, and SASSID). The Restormer model, which employs an encoder-decoder transformer architecture and progressive learning, stood out …
Deciphering The Contribution Of Microglia To Neurodegeneration In Friedreich's Ataxia, Sydney N. Gillette
Deciphering The Contribution Of Microglia To Neurodegeneration In Friedreich's Ataxia, Sydney N. Gillette
Master's Theses
Friedreich's ataxia (FRDA) is the most prevalent inherited ataxia, affecting one in every 50,000 individuals in the United States. This hereditary condition is caused by an abnormal GAA trinucleotide repeat expansion within the first intron of the frataxin gene resulting in decreased levels of the frataxin protein (FXN). Insufficient cellular frataxin levels results in iron accumulation, increased reactive oxygen species production and mitochondrial dysfunction. Tissues most heavily impacted are those most dependent on oxidative phosphorylation as an energy source and include the nervous system and muscle tissue. This is evident in the clinical phenotype which includes muscle weakness, ataxia, neurodegeneration …