27 citations · 31 across the 9 of their papers we have counts for
9 papers
Learning Brain Tumor Representation in 3D High-Resolution MR Images via Interpretable State Space Models
Qingqiao Hu, Daoan Zhang, Jiebo Luo +4
Learning meaningful and interpretable representations from high-dimensional volumetric magnetic resonance (MR) images is essential for advancing personalized medicine. While Vision…
SeLoRA: Self-Expanding Low-Rank Adaptation of Latent Diffusion Model for Medical Image Synthesis
Yuchen Mao, Hongwei Li, Wei Pang +3
The persistent challenge of medical image synthesis posed by the scarcity of annotated data and the need to synthesize `missing modalities' for multi-modal analysis, underscored th…
3D Vessel Graph Generation Using Denoising Diffusion
Chinmay Prabhakar, Suprosanna Shit, Fabio Musio +5
Blood vessel networks, represented as 3D graphs, help predict disease biomarkers, simulate blood flow, and aid in synthetic image generation, relevant in both clinical and pre-clin…
3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images
Alina F. Dima, Veronika A. Zimmer, Martin J. Menten +8
Automated segmentation of the blood vessels in 3D volumes is an essential step for the quantitative diagnosis and treatment of many vascular diseases. 3D vessel segmentation is bei…
Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images
Chinmay Prabhakar, Hongwei Bran Li, Johannes C. Paetzold +6
Multiple Sclerosis (MS) is a severe neurological disease characterized by inflammatory lesions in the central nervous system. Hence, predicting inflammatory disease activity is cru…
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta +57
Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists,…