YoloCurvSeg: You only label one noisy skeleton for vessel-style curvilinear structure segmentation

L Lin, L Peng, H He, P Cheng, J Wu, KKY Wong… - Medical Image …, 2023 - Elsevier
Weakly-supervised learning (WSL) has been proposed to alleviate the conflict between data
annotation cost and model performance through employing sparsely-grained (ie, point-, box …

Modal-aware visual prompting for incomplete multi-modal brain tumor segmentation

Y Qiu, Z Zhao, H Yao, D Chen, Z Wang - Proceedings of the 31st ACM …, 2023 - dl.acm.org
In the realm of medical imaging, distinct magnetic resonance imaging (MRI) modalities can
provide complementary medical insights. However, it is not uncommon for one or more …

Knowledge‐driven deep learning for fast MR imaging: Undersampled MR image reconstruction from supervised to un‐supervised learning

S Wang, R Wu, S Jia, A Diakite, C Li… - Magnetic …, 2024 - Wiley Online Library
Deep learning (DL) has emerged as a leading approach in accelerating MRI. It employs
deep neural networks to extract knowledge from available datasets and then applies the …

Contrast‐enhanced MRI synthesis using dense‐dilated residual convolutions based 3D network toward elimination of gadolinium in neuro‐oncology

AFI Osman, NM Tamam - Journal of Applied Clinical Medical …, 2023 - Wiley Online Library
Recent studies have raised broad safety and health concerns about using of gadolinium
contrast agents during magnetic resonance imaging (MRI) to enhance identification of active …

Diverse Data Generation for Retinal Layer Segmentation with Potential Structure Modelling

K Huang, X Ma, Z Zhang, Y Zhang… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
Accurate retinal layer segmentation on optical coherence tomography (OCT) images is
hampered by the challenges of collecting OCT images with diverse pathological …

Synthetic MRI in action: A novel framework in data augmentation strategies for robust multi-modal brain tumor segmentation

K Pani, I Chawla - Computers in Biology and Medicine, 2024 - Elsevier
Brain tumor diagnostics rely heavily on Magnetic Resonance Imaging (MRI) for accurate
diagnosis and treatment planning due to its non-invasive nature and detailed soft tissue …

OA-GAN: organ-aware generative adversarial network for synthesizing contrast-enhanced medical images

Y Yang, J Liu, G Zhan, Q Chen, F Wang… - Biomedical Physics …, 2024 - iopscience.iop.org
Contrast-enhanced computed tomography (CE-CT) images are vital for clinical diagnosis of
focal liver lesions (FLLs). However, the use of CE-CT images imposes a significant burden …