Real-World Low-Dose CT Image Denoising by Patch Similarity Purification
Z Song, L Xue, J Xu, B Zhang, C **… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Reducing the radiation dose in CT scanning is important to alleviate the damage to the
human health in clinical scenes. A promising way is to replace the normal-dose CT (NDCT) …
human health in clinical scenes. A promising way is to replace the normal-dose CT (NDCT) …
Optimizing Lung Cancer Detection in CT Imaging: A Wavelet Multi-Layer Perceptron (WMLP) Approach Enhanced by Dragonfly Algorithm (DA)
B Jamshidi, N Ghorbani… - arxiv preprint arxiv …, 2024 - arxiv.org
Lung cancer stands as the preeminent cause of cancer-related mortality globally. Prompt
and precise diagnosis, coupled with effective treatment, is imperative to reduce the fatality …
and precise diagnosis, coupled with effective treatment, is imperative to reduce the fatality …
SDCNN: Self-Supervised Disentangled Convolutional Neural Network for Low-Dose CT Denoising
Y Liu, H Shu, Q Chi, Y Zhang, Z Liu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Low-dose computed tomography (LDCT) reduces radiation exposure but suffers from high
noise, impacting image quality and diagnostic accuracy. Supervised learning has helped …
noise, impacting image quality and diagnostic accuracy. Supervised learning has helped …