Journal of Pathology Informatics (Jan 2014)

Histostitcher™: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework

  • Robert J Toth,
  • Natalie Shih,
  • John E Tomaszewski,
  • Michael D Feldman,
  • Oliver Kutter,
  • Daphne N Yu,
  • John C Paulus,
  • Ginaluca Paladini,
  • Anant Madabhushi

DOI
https://doi.org/10.4103/2153-3539.129441
Journal volume & issue
Vol. 5, no. 1
pp. 8 – 8

Abstract

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Context: Co-registration of ex-vivo histologic images with pre-operative imaging (e.g., magnetic resonance imaging [MRI]) can be used to align and map disease extent, and to identify quantitative imaging signatures. However, ex-vivo histology images are frequently sectioned into quarters prior to imaging. Aims: This work presents Histostitcher™, a software system designed to create a pseudo whole mount histology section (WMHS) from a stitching of four individual histology quadrant images. Materials and Methods: Histostitcher™ uses user-identified fiducials on the boundary of two quadrants to stitch such quadrants. An original prototype of Histostitcher™ was designed using the Matlab programming languages. However, clinical use was limited due to slow performance, computer memory constraints and an inefficient workflow. The latest version was created using the extensible imaging platform (XIP™) architecture in the C++ programming language. A fast, graphics processor unit renderer was designed to intelligently cache the visible parts of the histology quadrants and the workflow was significantly improved to allow modifying existing fiducials, fast transformations of the quadrants and saving/loading sessions. Results: The new stitching platform yielded significantly more efficient workflow and reconstruction than the previous prototype. It was tested on a traditional desktop computer, a Windows 8 Surface Pro table device and a 27 inch multi-touch display, with little performance difference between the different devices. Conclusions: Histostitcher™ is a fast, efficient framework for reconstructing pseudo WMHS from individually imaged quadrants. The highly modular XIP™ framework was used to develop an intuitive interface and future work will entail mapping the disease extent from the pseudo WMHS onto pre-operative MRI.

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