| PhD Seminar

Name of the Speaker: Mr. Srinivasa Karthik (EE21D032)
Guide: Prof. Mohanasankar Sivaprakasam
Co-Guide: Dr. Jayaraj Joseph
Online meeting link: https://meet.google.com/nrh-daib-phb
Date/Time: 29th December 2023 (Friday), 11:000 AM
Title: Wide field block face imaging using deep UV induced autofluorescence of the human brain

Abstract

Imaging large volume human brains at cellular resolution involve histological methods, including freezing and sectioning the tissue into large and thin slices, that can induce structural changes. A reference point prior to sectioning is needed to quantify these changes. In this seminar, a serial block face imaging (BFI) system is presented, which is custom designed for imaging large format cryosections, at sub-millimeter resolution, before they are subsequently imaged at sub-micron resolution. The BFI system uses 254 nm deep ultraviolet (UV-C) wavelength illumination, which ensures high contrast imaging of the brain tissue and highlights salient features of the brain. The BFI system can image large tissue blocks of dimensions 150 x 200 mm, at 70 μm per pixel resolution. A customized arrangement was developed to install the BFI setup within a cryomacrotome, and it has been used to image a large cryoblock of an adult human cerebellum and brainstem (~6 cm depth sectioned at 20 µm slice thickness with 2995 serial images) with precise optical focus during the continuous serial acquisition. The deep UV-C highlights several neuroanatomical regions, in particular the large fibre tracts within the brain including the cerebellar peduncles, and the corticospinal tract. The regional annotations demonstrate the advantage of improved contrast of the white matter tracts obtained using UV-C based imaging system relative to the broadband white light BFI. The improved contrast has also been quantified using multispectral images. The serial BFI images were used to create a 3D brain reference volume that can assist in the registration and alignment of the microscopic high-resolution histological tissue sections.