Assessment of glomerular patterns of injury by using artificial intelligence methods

Project implementation period: from 2020-09-01 to 2022-08-31es fondų investicijų veiksmų programa

Research fellow: Justinas Besusparis

Fellowship supervisor: prof. Arvydas Laurinavičius

The main objective of this project is to develop the methodologies for automated assessment of glomerular patterns of injury by using artificial intelligence technologies. The workflow includes: training of image analysis software for glomerular segmentation and detection of different histological patterns, extraction of morphometric and quantitative parameters to describe the activity and chronicity of glomerular damage, validation procedures and co-operation with foreign researchers. The main task is to improve visual assessment of glomerular diseases and objectify the level of glomerular injury by using digital image analysis which could be potentially applied for routine kidney pathology assessment. This work will explore novel approaches of artificial intelligence methods to pathology diagnosis. In practical terms, validated methods would allow further development of computer-assisted diagnosis and prognosis decision support tools to be integrated into laboratory information and digital pathology systems.

Funding: funded by European Social Fund (2014-2020) under the measure No 09.3.3-LMT-K-712 „Educating the society and strengthening the potential of human resources” activity „Development of Competences of Scientists, Other Researchers and Students Through Practical Research Activities“

 

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