De Medeiros Bruno,  Gatidis Sergios

Final Pr. ID: Poster #: SCI-005

Deep learning models have become instrumental in medical imaging, with a wide array of applications such as automated segmentation and diagnosis. However, the majority of these models are trained on adult imaging datasets, leading to underperformance when applied to the pediatric population. This discrepancy arises from anatomical differences between these populations, posing a significant challenge in fields requiring high precision like spine segmentation in Computed Tomography (CT) scans. Read More

Authors:  De Medeiros Bruno , Gatidis Sergios

Keywords:  Computed Tomography, Segmentation, Image Database