10-05-2016, 01:04 PM
Accurate measurement and classification of blood vessels could provide useful information to clinical diagnosis. Abnormalities in diameter of retinal blood vessels and presence of unusual
artefacts on retinal image are usually the first clinical finding in many retinal diseases, like diabetic retinopathy etc. Manual segmentation of retinal blood vessels is a long and tedious task
which also requires skill. That is why automatic delineation and classification of retinal vessels, and general evaluation of retinal images is the first step in the development of a computerised diagnostic system for ophthalmic disorders.
Objective:
To implement algorithms for segmentation and classification of retinal blood vessels in MATLAB for medical application. The final result of this work (amount will differ for BA and
MA) should comprise:
A comparison of existing state-of-the-art image processing techniques for medical evaluation of retinal images;
A working MATLAB program which is able to classify vessels into arteries and veins, calculate an average diameter for each, and find artefacts on retinal image which are sign of a retinal disease. On the base of obtained data the program should make a decision on the age and/or possible diseases.
A conclusion on advantages and disadvantages of each implemented image processing technique.
Tasks involved:
To investigate current blood vessel extraction techniques in retinal images and vascular models in general;
To learn image processing in MATLAB;
To make an algorithm for blood vessel segmentation and classification for diagnostic purposes;
To validate the algorithm by using publicly available databases of retinal images.
Requirements:
High self-motivation
Interest in image processing techniques
Participation in „Machine Vision“ course from MRT (KIT)
Experience in MATLAB is desirable
We provide
Supervisor who will supervise
Opportunity to practice image processing skills in on-the-edge-of-science application
The possibility to develop and pursue your own ideas within the project
artefacts on retinal image are usually the first clinical finding in many retinal diseases, like diabetic retinopathy etc. Manual segmentation of retinal blood vessels is a long and tedious task
which also requires skill. That is why automatic delineation and classification of retinal vessels, and general evaluation of retinal images is the first step in the development of a computerised diagnostic system for ophthalmic disorders.
Objective:
To implement algorithms for segmentation and classification of retinal blood vessels in MATLAB for medical application. The final result of this work (amount will differ for BA and
MA) should comprise:
A comparison of existing state-of-the-art image processing techniques for medical evaluation of retinal images;
A working MATLAB program which is able to classify vessels into arteries and veins, calculate an average diameter for each, and find artefacts on retinal image which are sign of a retinal disease. On the base of obtained data the program should make a decision on the age and/or possible diseases.
A conclusion on advantages and disadvantages of each implemented image processing technique.
Tasks involved:
To investigate current blood vessel extraction techniques in retinal images and vascular models in general;
To learn image processing in MATLAB;
To make an algorithm for blood vessel segmentation and classification for diagnostic purposes;
To validate the algorithm by using publicly available databases of retinal images.
Requirements:
High self-motivation
Interest in image processing techniques
Participation in „Machine Vision“ course from MRT (KIT)
Experience in MATLAB is desirable
We provide
Supervisor who will supervise
Opportunity to practice image processing skills in on-the-edge-of-science application
The possibility to develop and pursue your own ideas within the project