Author

Filippo Ruffini

3 papers indexed here

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Open access Sep 2026

Benchmarking foundation models for tumor segmentation across multiple cancer types

Tumor segmentation is a core task in medical image analysis, with direct implications for diagnosis, treatment planning, and disease monitoring. Whether promptable foundation models are mature enough for heterogeneous oncological scenarios remains an open question. We present a multi-cancer benchmark spanning lung, liv...

M. Tortora, Elena Mulero Ayllón, Filippo Ruffini et al. · Scientific Reports · 0 citations

#artificial intelligence May 2026

Cross Modality Image Translation In Medical Imaging Using Generative Frameworks

This work presents a reproducible benchmark for 3D I2I translation in oncological imaging that compares seven generative models: three Generative Adversarial Networks (Pix2Pix, CycleGAN, and SRGAN) and four latent models (Latent Diffusion Model, Latent Diffusion Model+ControlNet, Brownian Bridge, and Flow Matching).

G. Romoli, A. Capoccia, Filippo Ruffini et al. · arXiv.org · 1 citation

#artificial intelligence Preprint Sep 2026

Source Anchoring for Physical Consistency in Flow Matching Models

This work proposes Source Anchoring for Physical Consistency (SAPC), a Functional Flow Matching method that encodes the physical constraints into the source noise before generation begins, and identifies the source distribution as a key design choice for physically consistent generative modelling.

G. Romoli, Filippo Ruffini, P. Soda · 0 citations