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20232026
most citedA Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications

82 citations · 138 across the 10 of their papers we have counts for

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5 papers · 1 filter

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

Learning from Limited and Incomplete Data: A Multimodal Framework for Predicting Pathological Response in NSCLC

Alice Natalina Caragliano, Giulia Farina, Fatih Aksu +10

Major pathological response (pR) following neoadjuvant therapy is a clinically meaningful endpoint in non-small cell lung cancer, strongly associated with improved survival. Howeve…

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★ 1 cited

Handling Missing Modalities in Multimodal Survival Prediction for Non-Small Cell Lung Cancer

Filippo Ruffini, Camillo Maria Caruso, Claudia Tacconi +16

Accurate survival prediction in Non-Small Cell Lung Cancer (NSCLC) requires integrating clinical, radiological, and histopathological data. Multimodal Deep Learning (MDL) can impro…

cs.CV2025

From Alignment to Synthesis: Contrastive Volumetric Grounding for Text-to-CT Generation

Daniele Molino, Camillo Maria Caruso, Filippo Ruffini +2

Generating semantically controllable 3D CT volumes from radiology reports requires more than a rich text encoder, it requires vision-language alignment grounded in volumetric space…