학술논문
Enhanced Multiscale Human Brain Imaging by Semi-supervised Digital Staining and Serial Sectioning Optical Coherence Tomography.
Document Type
Author
Cheng S; Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, MA, 02215, USA.; Chang S; Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, MA, 02215, USA.; Li Y; Department of Electrical Engineering and Computer Sciences, University of California, Cory Hall, Berkeley, California, 94720, USA.; Novoseltseva A; Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA.; Lin S; Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, MA, 02215, USA.; Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA.; Wu Y; Department of Computer Science, Boston University, 665 Commonwealth Ave, Boston, MA, 02215, USA.; Zhu J; Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, MA, 02215, USA.; McKee AC; Boston University Alzheimer's Disease Research Center and CTE Center, Boston University, Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA.; Department of Neurology, Boston University, Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA.; VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, MA, 02130, USA.; Department of Psychiatry and Ophthalmology, Boston University School of Medicine, Boston, MA, 02118, USA.; Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, 02118, USA.; Rosene DL; Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts, USA.; Wang H; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, 02129, USA.; Bigio IJ; Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, MA, 02215, USA.; Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA.; Neurophotonics Center, Boston University, Boston, MA, 02215, USA.; Boas DA; Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, MA, 02215, USA.; Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA.; Neurophotonics Center, Boston University, Boston, MA, 02215, USA.; Tian L; Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, MA, 02215, USA.; Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA.; Neurophotonics Center, Boston University, Boston, MA, 02215, USA.
Source
Country of Publication: United States NLM ID: 101768035 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: Res Sq Subsets: PubMed not MEDLINE
Subject
Language
English
Abstract
A major challenge in neuroscience is to visualize the structure of the human brain at different scales. Traditional histology reveals micro- and meso-scale brain features, but suffers from staining variability, tissue damage and distortion that impedes accurate 3D reconstructions. Here, we present a new 3D imaging framework that combines serial sectioning optical coherence tomography (S-OCT) with a deep-learning digital staining (DS) model. We develop a novel semi-supervised learning technique to facilitate DS model training on weakly paired images. The DS model performs translation from S-OCT to Gallyas silver staining. We demonstrate DS on various human cerebral cortex samples with consistent staining quality. Additionally, we show that DS enhances contrast across cortical layer boundaries. Furthermore, we showcase geometry-preserving 3D DS on cubic-centimeter tissue blocks and visualization of meso-scale vessel networks in the white matter. We believe that our technique offers the potential for high-throughput, multiscale imaging of brain tissues and may facilitate studies of brain structures.
Competing Interests: Competing interests: The authors declare that they have no competing interests.
Competing Interests: Competing interests: The authors declare that they have no competing interests.