5 papers
CDPM-Align: Multi-Scale Guidance-Aligned Diffusion Pretraining for Robust Few-Shot Anatomical Landmark Detection
Roberto Di Via, Irina Voiculescu, Francesca Odone +1
Anatomical landmark detection is a fundamental task in medical image analysis supporting a wide range of diagnostic and interventional workflows. Although recent methods have achie…
Automated Landmark Detection for assessing hip conditions: A Cross-Modality Validation of MRI versus X-ray
Roberto Di Via, Vito Paolo Pastore, Francesca Odone +2
Many clinical screening decisions are based on angle measurements. In particular, FemoroAcetabular Impingement (FAI) screening relies on angles traditionally measured on X-rays. Ho…
Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing
Massimiliano Ciranni, Vito Paolo Pastore, Roberto Di Via +3
Deep learning model effectiveness in classification tasks is often challenged by the quality and quantity of training data whenever they are affected by strong spurious correlation…
Self-supervised pre-training with diffusion model for few-shot landmark detection in x-ray images
Roberto Di Via, Francesca Odone, Vito Paolo Pastore
Deep neural networks have been extensively applied in the medical domain for various tasks, including image classification, segmentation, and landmark detection. However, their app…
Is in-domain data beneficial in transfer learning for landmarks detection in x-ray images?
Roberto Di Via, Matteo Santacesaria, Francesca Odone +1
In recent years, deep learning has emerged as a promising technique for medical image analysis. However, this application domain is likely to suffer from a limited availability of…