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Project Contact:
José Manuel Fonseca

Bilena Almeida

Project Summary

For more than a century that the diagnosis of diseases such as cancer is based on the microscopic analysis of pathology slides. However, the use of conventional optical microscopes implies an inherently subjective process whose reports present important limitations. These limitations and the increasing emphasis on personalized medicine (implying faster, more accurate diagnosis) are leading pathology to become digital. Indeed, digital pathology presents several advantages that cannot be obtained using conventional optical microscopes.

The aim of this project is to provide pathologists with new software tools that can assist them in their daily work, providing greater efficiency and confidence in the performance of their duties leading to an improvement in the diagnostic quality.

In this sense, to facilitate the use of pathology digital images for clinical diagnosis, we developed the IPATHSCOPE viewer, an application to optimize the assisted analysis of hyper-resolution biopsy images. This tool, providing an image quality competitive with the one presented by the optical microscope and making available multiple navigation mechanisms based on ergonomic devices such as mouse, keyboard and joystick, have great potential to become a daily use tool for pathologists, allowing a significant reduction of their workload and a greater precision in their diagnosis.

IPATHSCOPE - Interface for assisted analysis of pathology digital images.

The key benefits of the interface can be summarized in the following features:

  • Image displayed at different magnification factors with improved quality by anti-aliasing pre-filtering;
  • Mechanism of overview + detail;
  • Multiple navigation mechanisms;
  • Realization and revision of annotations;
  • Statistical support tools allowing quantitative analysis;
  • Sub-images exportation;
  • Keyboard shortcuts.

In order to provide an assistant tool for the thyroid cancer diagnosis, we have also integrated in the viewer a nucleoids automatic segmentation algorithm on thyroid scraped slides in light field, which, by providing measures of specific characteristics of the morphology and homogeneity of the identified cells, provides the pathologist with an additional support and factual statistical bases for better evaluation of the state and the evolution of the disease.

Interface for nucleoids automatic segmentation on thyroid scraped slides sub-images in light field.


Disclaimer: This is a trial version of the application, optimized and recommended for computers which fulfill the following requirements:

  • Mac OS with screen resolution at least 1920 x 1200 and version above 10.11
  • Windows with screen resolutions at least 1920 x 1080;
  • Memory RAM at least 8 gigabytes.

Research Topics:
  • Virtual Microscopy
  • Digital Pathology
  • Hyper-Resolution
  • Image Processing
  • Downsampling
  • Segmentation