arXiv AI September 25, 2026 By Yantong Liu, Zheyu Zhang, Runpeng Liu, Mu Xitang, Seong-Yoon Shin, Hyun-Ae Lee

CrossScale-GLIO: Topology-Preserving Vision-Language Alignment of MRI and Whole-Slide Histopathology for Diffuse Glioma

CrossScale-GLIO is a multimodal framework that aligns magnetic resonance imaging (MRI) and whole‑slide histopathology of diffuse glioma by representing MRI as a tumor‑habitat graph and histology as a cell‑niche graph. Using a structure‑aware optimal transport objective anchored by diagnostic language, the method achieved high predictive performance on glioma subtyping and molecular markers, with a paired‑test subtype macro‑F1 of 0.789 and AUROCs ranging from 0.802 to 0.934. Pathologists found 81.2% of high‑mass habitat‑niche pairs biologically plausible, and experiments showed that preserving relational topology is essential for accurate cross‑scale correspondence.

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arXiv AI

Sep 18

Bridging Modalities on the Cortex: Surface-based MRI to PET Translation with a Diffusion Bridge

The paper introduces DB‑SUiT, a surface‑based diffusion bridge that translates cortical MRI to PET images directly on the cortical manifold. It employs a conditional spherical U‑shaped vision Transformer to capture multi‑scale surface features and long‑range dependencies while incorporating demographic and subcortical information. Evaluations on two dementia datasets show that the synthesized PET surfaces outperform MRI and PET volumes in automated classification and achieve high diagnostic accuracy in a blinded reader study.

By Yitong Li, Alexandra Samoylova, Fabian Bongratz, Timo Grimmer, Dennis M. Hedderich, Igor Yakushev, Christian Wachinger

llms diffusion computer-vision multimodal

arXiv Computation and Language

3d ago

Evidence-Bound Reasoning: Neuro-Semantic Verification of Biomedical AI in Glioblastoma Radiogenomics

arXiv:2610.08660v1 Announce Type: new Abstract: Background: Biomedical AI can generate plausible explanations without reliably verifying whether each statement is supported by patient-specific eviden...

By Mariya Miteva, Maria Nisheva-Pavlova

llms benchmarks

arXiv AI

Jul 28

Post-Operative Glioma Segmentation via Loss Stabilization, Normalization and Subspace Attention

arXiv:2607. 22749v1 Announce Type: cross Abstract: Tracking residual tumor after surgery is essential for catching recurrence early, but automating post-operative glioma segmentation remains a difficult task.

By Alexandru Cri\c{s}an, Diana Borza

llms computer-vision benchmarks

arXiv Machine Learning

Jun 30

TRACE: A Concept Bottleneck Model for Longitudinal 3D Glioblastoma Response Assessment

arXiv:2606. 30313v1 Announce Type: cross Abstract: Longitudinal glioblastoma response assessment requires comparing subtle tumor changes across MRI time points using structured clinical criteria such as RANO.

By Alia Tarek, Hamsa Saberr, Hamza Elghonemy, Youssef Afify, Tamer Basha, Omair Shahzad Bhatti, Abdulrahman M. Selim, Hasan Md Tusfiqur Alam Daniel Sonntag

multimodal benchmarks

arXiv Computer Vision

Sep 2

Conditional Flow Matching for Cross-Field MRI Harmonisation

arXiv:2609.00960v1 Announce Type: new Abstract: Magnetic resonance images of the same subject look markedly different across field strengths, which complicates the comparison and pooling of data acro...

By Baris Imre, Aram Salehi, Levente Baljer, Andrew Webb, Marius Staring, Efe Ilicak

diffusion fine-tuning safety

arXiv Computer Vision

2d ago

STRIDE: Spatial-Temporal Representation for Interval-conditioned Disease Evolution in Longitudinal Glioblastoma MRI

arXiv:2610.08848v1 Announce Type: cross Abstract: Glioblastoma (GBM), an aggressive primary brain tumor, is routinely monitored with longitudinal MRI after treatment. Distinguishing stable disease (S...

By Wenhao Guo, Changchang Yin, Pierre Giglio, Weidan Cao, Ping Zhang, Golrokh Mirzaei

llms