An Experimental Platform for Tomographic Reconstruction of Tissue Images in Brightfield Microscopy

Sensors (Basel). 2023 Nov 23;23(23):9344. doi: 10.3390/s23239344.

Abstract

(1) Background: Reviewing biological material under the microscope is a demanding and time-consuming process, prone to diagnostic pitfalls. In this study, a methodology for tomographic imaging of tissue sections is presented, relying on the idea that each tissue sample has a finite thickness and, therefore, it is possible to create images at different levels within the sample, revealing details that would probably not be seen otherwise. (2) Methods: Optical slicing was possible by developing a custom-made microscopy stage controlled by an ARDUINO. The custom-made stage, besides the normal sample movements that it should provide along the x-, y-, and z- axes, may additionally rotate the sample around the horizontal axis of the microscope slide. This rotation allows the conversion of the optical microscope into a CT geometry, enabling optical slicing of the sample using projection-based tomographic reconstruction algorithms. (3) Results: The resulting images were of satisfactory quality, but they exhibited some artifacts, which are particularly evident in the axial plane images. (4) Conclusions: Using classical tomographic reconstruction algorithms at limited angles, it is possible to investigate the sample at any desired optical plane, revealing information that would be difficult to identify when focusing only on the conventional 2D images.

Keywords: 3D tissue volume imaging; cancer; histopathology; optical microscopy.

MeSH terms

  • Algorithms
  • Artifacts
  • Image Processing, Computer-Assisted / methods
  • Imaging, Three-Dimensional / methods
  • Microscopy*
  • Tomography*

Grants and funding

This research received no external funding.