Description
This presentation from the ISTA 2024 conference held in Nashville captures a technical discussion about predicting post-operative muscle motions using static shape modeling. The speakers delve into the complexities of how muscle dynamics may differ when lying down in a scanner versus standing positions, hinting at the potential for changes in muscle shape and volume that could impact their predictions. The focus appears to be on creating automated measurements suitable for machine learning applications, emphasizing the importance of objective data versus manual inputs in enhancing predictive models. Furthermore, they touch on the physiological and biomechanical foundations of their findings, exploring whether combining their radiomic features with physiological models could improve accuracy. Overall, the dialogue highlights the challenges and opportunities in linking advanced feature extraction with practical applications in medicine, particularly in the realm of oncology.