Using Python libraries, I built a 3D interactive visualization tool for displaying radiation doses delivered to the patient’s body during radiotherapy. In addition to visualizing 5-dimensional data (x, y, z, organ, radiation dose), this tool provided a range of useful features. These features included descriptive statistics for each organ and selected regions, dose-volume histograms, in-depth voxel-level analysis, and more. The tool was capable of handling over 3 million data points and significantly aided in comprehending the treated areas in radiotherapy.

This 3D interactive visualization tool significantly contributes to the creation of comprehensive representations of voxelized heart-dose reconstruction. Its contribution is featured in the publication by Chounta et al. (2023)[1], enhancing the visual context and providing a deeper understanding of intricate medical data.

REFERENCES
[1] Chounta S., Allodji R., Vakalopoulou M., Bentriou M., Do D.T., De Vathaire F., Diallo I., Fresneau B., Charrier T., Zossou V., Christodoulidis S., Lemler S., Letort Le Chevalier V. Dosiomics-Based Prediction of Radiation-Induced Valvulopathy after Childhood Cancer. Cancers (Basel). 2023 Jun 8;15(12):3107. doi: 10.3390/cancers15123107. PMID: 37370717; PMCID: PMC10296033.