1. Mobile Application for Ocular Tumor Detection and Classification
The project titled "Mobile Application for Ocular Tumor Detection and Classification Using Machine Learning and Image Processing Techniques," prepared by our student Mustafa Alperen YILDIRIM under the supervision of Assoc. Prof. Dr. M. Fatih IŞIK, was among the supported projects. The project aims to develop a mobile-based software system that detects intraocular and periocular tumors via a camera and performs an analysis based on the obtained image. The analysis results are expected to contribute significantly to the doctor's ability to provide a quick diagnosis. The planned application will target the detection of 6 types of tumors, both inside and around the eye. The application will use datasets with machine learning and image processing techniques to detect and classify the tumors. A mobile application interface will be designed to present the detection software in a user-friendly manner. Project studies and testing will be conducted in collaboration with doctors specializing in Ocular Tumors at the Hitit University Faculty of Medicine. The goal of this project is to detect tumors inside and around the eye at an earlier stage, allowing for early diagnosis before the tumors reach dangerous sizes.
2. Monitoring Forests with Image Processing Techniques
The project titled "Monitoring Forests with Image Processing Techniques," prepared by our student Muhammed ÖZTÜRK under the supervision of Assist. Prof. Dr. Ela BULUT, was among the projects supported by TÜBİTAK. The project aims to determine the relative percentage of greenery between two images taken at different times for a specific area using image processing techniques, algorithms, and libraries. To determine these percentages, satellite images will initially be used to report changes that have occurred from the past to the present. Subsequently, using a camera and a drone (to be acquired with project support), green areas will be detected by applying image processing to an aerial photograph taken of a determined region. This prototype will allow us to photograph the same region at desired intervals and observe changes in the amount of tree coverage. The project will enable the identification of areas where trees are diminishing, allowing relevant units and authorities to be informed about the necessary precautions. This will facilitate the planting of new trees in place of the missing ones and closer monitoring of these areas to determine the factors causing the loss of trees. This project aims to increase environmental awareness and contribute to the protection of forests.
3. Design of an Advanced Vascular Imaging Device
The project titled "Design of an Advanced Vascular Imaging Device," prepared by our students Merve ŞEN, Feyza Nur KARADAŞ, and Mustafa ÖZCAN under the supervision of Assist. Prof. Dr. Kenan GENÇOL, was supported by TÜBİTAK. Finding veins during venipuncture in hospitals is often very difficult, particularly in children, the elderly, obese individuals, severe burn cases, or people with dark skin. This can lead to psychological distress in patients and prolong their treatment processes. To eliminate these disadvantages, the design and widespread use of vascular imaging devices are crucial. The project aims to design a more stable and accurate device for this purpose by utilizing infrared – visible spectrum conversion. The implementation part of the project involves hardware design using a Raspberry Pi microcomputer with a Raspberry Pi camera, IR LEDs, and a Kodak Wratten 87C filter, and software design implemented in Python using the OpenCV library.
These projects, prepared by our department's faculty members and students, are expected to introduce significant innovations. We congratulate the students whose projects were accepted and the faculty members who supported them, and we wish them continued success.
