5 papers
Generalist Models in Medical Image Segmentation: A Survey and Performance Comparison with Task-Specific Approaches
Andrea Moglia, Matteo Leccardi, Matteo Cavicchioli +4
Following the successful paradigm shift of large language models, leveraging pre-training on a massive corpus of data and fine-tuning on different downstream tasks, generalist mode…
MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Classification and Detection
Andrea Moglia, Elia Clement Nastasio, Luca Mainardi +1
Problem: Pancreas radiological imaging is challenging due to the small size, blurred boundaries, and variability of shape and position of the organ among patients. Goal: In this wo…
Optimized two-stage AI-based Neural Decoding for Enhanced Visual Stimulus Reconstruction from fMRI Data
Lorenzo Veronese, Andrea Moglia, Luca Mainardi +1
AI-based neural decoding reconstructs visual perception by leveraging generative models to map brain activity, measured through functional MRI (fMRI), into latent hierarchical repr…
Cascade learning in multi-task encoder-decoder networks for concurrent bone segmentation and glenohumeral joint assessment in shoulder CT scans
Luca Marsilio, Davide Marzorati, Matteo Rossi +4
Osteoarthritis is a degenerative condition affecting bones and cartilage, often leading to osteophyte formation, bone density loss, and joint space narrowing. Treatment options to…
Deep Learning for Pancreas Segmentation: a Systematic Review
Andrea Moglia, Matteo Cavicchioli, Luca Mainardi +1
Pancreas segmentation has been traditionally challenging due to its small size in computed tomography abdominal volumes, high variability of shape and positions among patients, and…