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20242026
most citedBenchmarking Foundation Models and Parameter-Efficient Fine-Tuning for Prognosis Prediction in Medical Imaging

5 citations · 9 across the 20 of their papers we have counts for

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cs.CV2026

Compositional Cross-Modality Translation via Whole-Volume Multitask Latent Flow Matching

Daniele Molino, Alessio Zoboli, Camillo Maria Caruso +2

Cross-modality medical image translation can reduce the burden of multi-modal acquisitions, yet the field remains constrained by two coupled limitations: methods operate on 2D slic…

cs.CV2026

SHOVIR: A Benchmark for Evaluating Vision Shortcut Learning in Radiology Report Generation

Filippo Ruffini, Marco Salmé, Rosa Sicilia +2

Current evaluation protocols for Vision-Language Models (VLMs) in Radiology Report Generation (RRG) rely on report-level metrics that measure lexical overlap or aggregate clinical…

cs.CV2026

Retrieval-Augmented Anatomical Guidance for Text-to-CT Generation

Daniele Molino, Camillo Maria Caruso, Paolo Soda +1

Text-conditioned generative models for volumetric medical imaging provide semantic control but lack explicit anatomical guidance, often resulting in outputs that are spatially ambi…

cs.CV2026

Cross Modality Image Translation In Medical Imaging Using Generative Frameworks

Giulia Romoli, Alessia Capoccia, Filippo Ruffini +20

Medical image-to-image (I2I) translation enables virtual scanning, i.e. the synthesis of a target imaging modality from a source one without additional acquisitions. Despite growin…

cs.CV2026

Multimodal Stepwise Clinically-Guided Attention Learning for Pathological Complete Response Prediction in Breast Cancer

Alice Natalina Caragliano, Valerio Guarrasi, Michela Gravina +2

Pathological complete response (pCR) is a key prognostic factor in breast cancer patients undergoing neoadjuvant therapy, strongly associated with long-term survival and treatment…

cs.CV2026

Virtual Scanning for NSCLC Histology: Investigating the Discriminatory Power of Synthetic PET

Fatih Aksu, Laura Ciuffetti, Francesco Di Feola +6

Accurate histological differentiation between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is critical for personalized treatment in non-small cell lung cancer (NSCLC). W…