Miaquant, a novel system for automatic segmentation, measurement, and localization comparison of different biomarkers from serialized histological slices

Elena Casiraghi, Mara Cossa, Veronica Huber, Matteo Tozzi, Licia Rivoltini, Antonello Villa, Barbara Vergani

Research output: Contribution to journalArticle


In the clinical practice, automatic image analysis methods quickly quantizing histological results by objective and replicable methods are getting more and more necessary and widespread. Despite several commercial software products are available for this task, they are very little flexible, and provided as black boxes without modifiable source code. To overcome the aforementioned problems, we employed the commonly used MATLAB platform to develop an automatic method, MIAQuant, for the analysis of histochemical and immunohistochemical images, stained with various methods and acquired by different tools. It automatically extracts and quantifies markers characterized by various colors and shapes; furthermore, it aligns contiguous tissue slices stained by different markers and overlaps them with differing colors for visual comparison of their localization. Application of MIAQuant for clinical research fields, such as oncology and cardiovascular disease studies, has proven its efficacy, robustness and flexibility with respect to various problems; we highlight that, the flexibility of MIAQuant makes it an important tool to be exploited for basic researches where needs are constantly changing. MIAQuant software and its user manual are freely available for clinical studies, pathological research, and diagnosis.

Original languageEnglish
Article number2838
Pages (from-to)270-275
Number of pages6
JournalEuropean Journal of Histochemistry
Issue number4
Publication statusPublished - Nov 2 2017



  • Artificial intelligence
  • Digital image processing
  • Histochemical and immunohistochemical image analysis
  • Statistical analysis

ASJC Scopus subject areas

  • Biophysics
  • Histology
  • Cell Biology

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