UR-CarA-Net: a cascaded framework with uncertainty regularization for automated segmentation of carotid arteries on black blood MR images
We present a fully automated method for carotid artery (CA) outer wall segmentation in black
blood MRI using partially annotated data and compare it to the state-of-the-art reference …
blood MRI using partially annotated data and compare it to the state-of-the-art reference …
PDC-Net: parallel dilated convolutional network with channel attention mechanism for pituitary adenoma segmentation
Q Zhang, J Cheng, C Zhou, X Jiang, Y Zhang… - Frontiers in …, 2023 - frontiersin.org
Accurate segmentation of the medical image is the basis and premise of intelligent
diagnosis and treatment, which has a wide range of clinical application value. However, the …
diagnosis and treatment, which has a wide range of clinical application value. However, the …
[HTML][HTML] Deep learning-based carotid plaque ultrasound image detection and classification study
H Zhang, F Zhao - Reviews in Cardiovascular Medicine, 2024 - pmc.ncbi.nlm.nih.gov
Background: This study aimed to develop and evaluate the detection and classification
performance of different deep learning models on carotid plaque ultrasound images to …
performance of different deep learning models on carotid plaque ultrasound images to …
[PDF][PDF] Deep learning for carotid artery segmentation in stroke-at-risk patients
E Lavrova, Z Salahuddin, HC Woodruff… - … with handcrafted and … - orbi.uliege.be
We present a fully automated method for carotid artery (CA) outer wall segmentation in black
blood MRI using partially annotated data and compare it to the state-of-the-art reference …
blood MRI using partially annotated data and compare it to the state-of-the-art reference …