CT Image
Computed tomography (CT) imaging produces detailed 3D images of the body, crucial for diagnosis and treatment planning across various medical specialties. Current research emphasizes improving CT image analysis through deep learning, focusing on architectures like U-Nets, Vision Transformers, and diffusion models for tasks such as organ segmentation, lesion detection, and image enhancement. These advancements aim to increase diagnostic accuracy, improve treatment planning, reduce radiation exposure, and enable more efficient workflows in clinical settings.
Papers
WIA-LD2ND: Wavelet-based Image Alignment for Self-supervised Low-Dose CT Denoising
Haoyu Zhao, Yuliang Gu, Zhou Zhao, Bo Du, Yongchao Xu, Rui Yu
COVID-19 detection from pulmonary CT scans using a novel EfficientNet with attention mechanism
Ramy Farag, Parth Upadhyay, Yixiang Gao, Jacket Demby, Katherin Garces Montoya, Seyed Mohamad Ali Tousi, Gbenga Omotara, Guilherme DeSouza