8 papers
ORCA: ORgan-Centroid Aggregation for Training-Free 3D CT Visual Token Compression
Renjie Liang, Zijian Xu, Jinqian Pan +6
A 3D CT scan entering a vision-language model produces a long sequence of visual tokens, often thousands to tens of thousands per volume, and this sequence must be compressed befor…
When Do Cheap Probes Predict Expensive Training? Probing 3D-CT Encoders for Text Generation
Renjie Liang, Zijian Xu
Building a 3D CT vision language model begins with a choice of which image encoder to build on. Today that choice is made by fine-tuning every candidate through the full language m…
An Interpretable Deep Learning Framework for Discovery and Clinical Validation of Deep Radiomic Signatures in Tumor Classification
Chengkun Sun, Jinqian Pan, Renjie Liang +7
Imaging signatures are quantitative features extracted from medical images that provide clinically meaningful information for tumor diagnosis, characterization, prognosis, and trea…
Multi-Granularity 3D Kidney Lesion Characterization from CT Volumes
Renjie Liang, Zhengkang Fan, Jinqian Pan +4
Radiology reports describe kidney lesions by type, size, enhancement, and attenuation, yet existing 3D methods predict only at the patient or organ level. We reformulate kidney CT…
OphMAE: Bridging Volumetric and Planar Imaging with a Foundation Model for Adaptive Ophthalmological Diagnosis
Tienyu Chang, Zhen Chen, Renjie Liang +9
The advent of foundation models has heralded a new era in medical artificial intelligence (AI), enabling the extraction of generalizable representations from large-scale unlabeled…
Beyond the Embedding Bottleneck: Adaptive Retrieval-Augmented 3D CT Report Generation
Renjie Liang, Yiling Ma, Yang Xing +6
Automated radiology report generation from 3D CT volumes often suffers from incomplete pathology coverage. We provide empirical evidence that this limitation stems from a represent…