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NET-IBA-2

Native/Engineered Tissue Image-Based structural and histopathology Analysis (NET-IBA)

Brief description

Tema: NET-IBA, sviluppo di algoritmi e metodi automatici per l’analisi strutturale e morfologica di tessuti nativi e scaffolds. L’istopatologia ed i metodi di analisi quantitativa di struttura su base immagine sono al momento scarsamente sviluppati in modo integrato. Gran parte delle valutazioni in istologia avvengono ancora sulla base di stime qualitative o semi-qualitative. Analogamente, i metodi di analisi strutturale sulla base di immagine, sviluppati in contesti di scienza dei materiali, trascurano svariate metriche quantitative per  micro e meso architettura. Questa linea di ricerca si posiziona all’interfaccia tra queste due discipline nel tentativo di fornire nuovi strumenti di indagine sia in ambito clinico che in ambito scienza dei materiali.

Impact:

The software tools we developed and that we are tryaing to advance have the potential to impact on two main categories of problems: 

– quantitative histology, potential applications include: biomaterial-host interactions, evaluation of drugs effects on tissue, inflammatory response evaluation, oncology, tissue elaboration in vitro and in vivo, big data;

– morphological analysis of micro and nano-structured materials, potential applications within the context of chemical, process engineering or material science, include: process control, process characterization, structure-function characterization.

Pipeline

  • CLINICAL
    NEED
  • DISEASES
    ANALYSIS
  • DISCOVERY
  • PRECLINICAL
    VALIDATION
  • PRECLINICAL
    DEVELOPMENT
  • CLINICAL
    STUDIES
NET-IBA: Blood vessel detection algorithm on immunohistochemical staining. Accurate identification and quantification of blood vessels can be labour intensive, time consuming and heavly dependet on the operator experience. An automated, objective method has been developed and validated, the block diagram illustrates the structure of the algorithm. (from left to right): a) input image, b) filtering and thresholding on red or green color channels, c1) detection of connected components , c2) morphological segmentation based on size and shape, c3) additional detection of connected components, d) segmentation criteria in c1,c2,c3 are combined together using morphological operators, e) labeling of connected components , f) algorithm’ result including vessel area quantification and spatial distribution (right)

Principal Investigator

Contact

adamore@fondazionerimed.com

Team di progetto:

Therapeutic area:

Products:
ATMP – Medical devices & tissue engineering

Collaborations:
University of Pittsburgh, PA
Università degli Studi di Palermo, Italia

   Scarica il pdf del progetto

Publications

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