32 citations · 122 across the 14 of their papers we have counts for
6 papers · 1 filter
A Multimodal and Multi-centric Head and Neck Cancer Dataset for Segmentation, Diagnosis and Outcome Prediction
Numan Saeed, Salma Hassan, Shahad Hardan +40
We present a publicly available multimodal dataset for head and neck cancer research, comprising 1123 annotated Positron Emission Tomography/Computed Tomography (PET/CT) studies fr…
Multi-Task Diffusion Approach For Prediction of Glioma Tumor Progression
Aghiles Kebaili, Romain Modzelewski, Jérôme Lapuyade-Lahorgue +3
Glioma, an aggressive brain malignancy characterized by rapid progression and its poor prognosis, poses significant challenges for accurate evolution prediction. These challenges a…
Mamba Based Feature Extraction And Adaptive Multilevel Feature Fusion For 3D Tumor Segmentation From Multi-modal Medical Image
Zexin Ji, Beiji Zou, Xiaoyan Kui +3
Multi-modal 3D medical image segmentation aims to accurately identify tumor regions across different modalities, facing challenges from variations in image intensity and tumor morp…
Global and Local Mamba Network for Multi-Modality Medical Image Super-Resolution
Zexin Ji, Beiji Zou, Xiaoyan Kui +2
Convolutional neural networks and Transformer have made significant progresses in multi-modality medical image super-resolution. However, these methods either have a fixed receptiv…
Self-Prior Guided Mamba-UNet Networks for Medical Image Super-Resolution
Zexin Ji, Beiji Zou, Xiaoyan Kui +2
In this paper, we propose a self-prior guided Mamba-UNet network (SMamba-UNet) for medical image super-resolution. Existing methods are primarily based on convolutional neural netw…
Medical Image Synthesis with Context-Aware Generative Adversarial Networks
Dong Nie, Roger Trullo, Caroline Petitjean +2
Computed tomography (CT) is critical for various clinical applications, e.g., radiotherapy treatment planning and also PET attenuation correction. However, CT exposes radiation dur…