Nerves segmentation and dendritic cells detection in IVCM images – DCN

Seed project: Nerves segmentation and dendritic cells detection in IVCM images – DCN

Automatic segmentation of nerves and detection of dendritic cells to provide accurate density measurements, aiding doctors in making informed treatment decisions.

Picture 1: IVCM image from an eye with nerve fibers Picture 2: IVCM image from an eye with dendritic cells.

Project information

Project manager
Alisa Lincke
Other project members
Jenny Roth, Antonio Macedo, Neil Lagali, Welf Löwe, Yan Song, Meichen Ji
Participating organisations
Linköping University, Linnaeus University
Financier
Linnaeus University Centre for Data Intensive Sciences and Applications (DISA)
Timetable
January–June 2025
Subject
Computer Science (Department of Computer Science and Media Technology, Faculty of Technology)
Research Group
Linnaeus University Centre for Data Intensive Sciences and Applications (DISA)

More about the project

In vivo confocal microscopy (IVCM) is a valuable imaging technique for studying the cornea's cellular structure, particularly for assessing nerves and immune cells such as dendritic cells. Nerve segmentation in IVCM images allows for the detailed analysis of the corneal nerves, which is essential for assessing the health of the corneal nerve network. Changes in nerve structure, density, or branching patterns can indicate various conditions, including diabetes, dry eye disease, Acanthamoeba keratitis, and other conditions.

By segmenting the nerves, we can quantify characteristics like nerve fiber length and density, providing objective metrics to monitor disease progression or therapeutic effects. Counting dendritic cells in IVCM images are crucial because an increased density of dendritic cells can be linked to corneal inflammation, infections, immune system activation and other conditions. In both nerves and dendritic cells, changes in density and structure over time can be key indicators of how a disease is progressing or how a the patient is responding to treatment.

Our previous study on corneal nerve fibers after mild COVID-19 has utilized the ImageJ image analysis software to compute nerve and dendritic cell density in selected images from 130 individuals (100 with mild COVID-19 infection and persistent ocular symptoms and 30 individuals without ocular symptoms as the control group). ImageJ is a powerful tool for medical image analysis, but it still requires manual annotation of nerve structures and dendritic cells for each selected image, typically around 10 images (5 for the left eye and 5 for the right eye) per individual, resulting in approximately 2600 images in total for our dataset. Furthermore, medical researchers rely on these representative 10 images, which may not always provide the most optimal assessment. Recent studies on nerve segmentation and dendritic cell detection using deep learning have demonstrated promising results in automating this process.

The overall objective of our research is to extend our DSS to automatically segment nerves and detect dendritic cells using deep learning, and compute their density, providing the treating doctor with reliable and accurate measures of the nerve and dendritic cell parameters, which will support them in treatment decisions, such as giving anti-inflammatory drugs. The main outcome of this seed project is an extended DSS with nerves segmentation and dendritic cell density calculation, which increases the efficiency of assessing IVCM images for medical researchers and clinical researchers, and potentially improve the diagnosis of ocular surface disease associated with corneal nerves and dendritic cells.

What is a seed project?

A seed project is a minor project funded by a knowledge environment or a research group at the university. The aim is to launch and promote excellent research. Depending on the financier, a seed project may be to idenfify new or deepen existing collaborations, preferably cross-disciplinary ones, to explore possible research issues in a feasibility study, to collect empirical material, or to write an application for external funding.

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