3 papers
cs.CV2025
PET Head Motion Estimation Using Supervised Deep Learning with Attention
Zhuotong Cai, Tianyi Zeng, Jiazhen Zhang +8
Head movement poses a significant challenge in brain positron emission tomography (PET) imaging, resulting in image artifacts and tracer uptake quantification inaccuracies. Effecti…
cs.LG2025
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation
Tal Zeevi, Ravid Shwartz-Ziv, Yann LeCun +2
Accurate uncertainty estimation is crucial for deploying neural networks in risk-sensitive applications such as medical diagnosis. Monte Carlo Dropout is a widely used technique fo…
eess.IV2025
Head Motion Degrades Machine Learning Classification of Alzheimer's Disease from Positron Emission Tomography
Eléonore V. Lieffrig, Takuya Toyonaga, Jiazhen Zhang +1
Brain positron emission tomography (PET) imaging is broadly used in research and clinical routines to study, diagnose, and stage Alzheimer's disease (AD). However, its potential ca…