Augmented Reality for Health Monitoring Laboratory

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Artificial Intelligence-assisted near-infrared fluorescence angiography with indocyanine green after colorectal resections



Application field

Laparoscopic surgery for colorectal cancer


Artificial Intelligence (AI), Computer Vision, Data Analysis


Development of artificial intelligence-based analysis method in indocyanine green (ICG) angiography to perform real-time perfusion analysis:

  • Identification of the optimal line for cancer resection


  • Assessment of the goodness of the vascularization

The AI techniques applied to near-infrared fluorescence angiography with indocyanine green is proposed as objective method to support surgeons in their decision-making processes, improving treatment and post-operative complications prevention.


  • Identification of appropriate tracker algorithms to enable fast and accurate tracking of the

selected region of interest.

  • Data pre-processing (e.g., appropriate color space for analysis) to make it suitable for the machine learning system.
  • Design and implementation of AI systems for the evaluation of bowel perfusion during colorectal surgery.


  • Improving the accuracy of the system using temporal aspect and variation of ICG fluorescence intensity over time.
  • Developing AI systems for the prediction of the optimal resection line in laparoscopic surgery for colorectal cancer.
  • Developing algorithms on portable devices with reduced computational power and memory capacity.


  • Arpaia, P., Bracale, U., Corcione, F., De Benedetto, E., Di Bernardo, A., Di Capua, V., Duraccio, L., Peltrini, R. and Prevete, R., 2022. Assessment of blood perfusion quality in laparoscopic colorectal surgery by means of Machine Learning. Scientific Reports, 12(1), pp.1-9.



Augmented Reality for Health Monitoring Laboratory

80100 Naples (ITALY) - Via Claudio, 21 - DIETI block
Tel  (+39) 081 123456 -  Fax (+39) 081 654321

80100 Naples (ITALY) - Via Claudio, 21
Tel (+39) 081 123456
Fax (+39) 081 654321
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