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_aMaria Ysabelle G. Celestra, Marc Czar F. Guitierrez, Cseth Marcus A. Martillano.
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_aAn Improved ray casting algorithm applied in rendering medical images.
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_aunmediated
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_aUndergraduate Thesis : (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2024.
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_aABSTRACT: The study aimed to enhance the ray casting algorithm used in converting 3D medical imagery into 2D representations, addressing challenges such as visual artifacts, slow rendering speeds, and high resource requirements. This modification aimed to expedite the process, providing medical professionals and students with quicker access to visual representations, thereby efficiency in critical tasks like research and treatment planning. To achieve this, 3D samples containing mesh data from medical studies were collected. These samples were used to simulate both the traditional and modified versions of the algorithm, and their rendering speeds were recorded usinga profiler. Data was presented in histogram format, and a apired t-test was conducted to assess the significance of differences between the two algorithm versions. The results demonstrated improvements in reducing visual artifacts, albeit not completely. The modified version achieved an average rendering speed of 46.40 milliseconds, compared to the current algorithm's average of 51.24 milliseconds, indicating a reduction in execution times by approximately 9.45%. Additionally, the modified algorithm decreased the memory requirement from 0.73 gigabytes to 0.68 gigabytes, marking a reduction of approximately 6.85%. The paired t-test analysis confirmed a statistically significant speedup in rendering. In conclusion, the modified ray casting algorithm showcased a significant enhancement in rendering speed, validated by the paired t-test. This improvement holds promise for increased efficiency in rendering 2D medical images, benefiting medical professionals significantly. The research implications are broad, extending to improved rendering efficiency for medical professionals, advancements in medical imaging, enhanced usability, and practical insights for clinical settings, ultimately contributing to advancements in medical technology and patient care.
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