Browsing by Author "Haamer, Rain Eric, juhendaja"

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Automated Detection and Quantification of Stomata
(Tartu Ülikool, 2024) Gorbachenko, Ivan; Hõrak, Hanna, juhendaja; Haamer, Rain Eric, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
This thesis presents an approach for the automated detection and quantification of stomata using machine learning techniques. The study focuses on employing the YOLOv8 model to analyse video data of leaf epidermal imprints, significantly improving the efficiency and accuracy of stomatal detection compared to traditional manual methods. The results highlight the model's ability to handle varying focal depths within video frames, ensuring consistent stomatal counts. Future research directions include expanding the dataset and incorporating advanced image analysis techniques to further enhance detection accuracy.
Automating assessment of silver-enhanced in situ hybridization for evaluation of cancer properties
(Tartu Ülikool, 2023) Kuklianov, Danila; Haamer, Rain Eric, juhendaja; Haamer, Sisi Carmen, juhendaja
To correctly assess breast cancer properties, doctors have to compare and evaluate histopathological slides stained for the presence of certain proteins; in the event that the initial evaluation is inconclusive, additional assessment is done. The assessment is necessary to accurately determine the type of cancer and select fitting treatment that increases the likelihood of the patient’s recovery. In this paper, approaches to automate different steps of this assessment are explored with the immediate goal of implementing an end-to-end algorithm pipeline capable of performing this task with minimal human input, with the potential goal of incorporating this pipeline into an existing larger slide processing software.
Gamification of a medical learning application VRAna
(Tartu Ülikool, 2023) Pisetskaya, Darya; Haamer, Rain Eric, juhendaja
As the quality of anatomy education is declining worldwide, faculties need to come up with new ways to engage and motivate students. Gamification is a growing trend in various fields including education, and can be an efficient instrument to help students study theoretical information. This work focuses on the gamification of a medical learning application VRAna by introducing several quiz scenarios for memorizing anatomical structures on the bones. The created games can be used as a supplementary tool for learning skeletal anatomy.