Intrathoracic airway segmentation in computed tomography is a prerequisite for various respiratory disease analyses such as chronic obstructive pulmonary disease, asthma and lung cancer. Due to the low imaging contrast and noises execrated at periphe...
Multi-modal prompt learning is a high-performance and cost-effective learning paradigm, which learns text as well as image prompts to tune pre-trained vision-language (V-L) models like CLIP for adapting multiple downstream tasks. However, recent meth...
IEEE transactions on neural networks and learning systems
Dec 2, 2024
Accurate lung lesion segmentation from computed tomography (CT) images is crucial to the analysis and diagnosis of lung diseases, such as COVID-19 and lung cancer. However, the smallness and variety of lung nodules and the lack of high-quality labeli...
Journal of applied clinical medical physics
Dec 1, 2024
PURPOSE: The complexity of convolutional neural networks (CNNs) can lead to improved segmentation accuracy in medical image analysis but also results in increased network complexity and training challenges, especially under resource limitations. Conv...
The human-brain is a vital and complicated organ within the body. Identifying brain-related diseases can be challenging. Typically, Magnetic Resonance Imaging (MRI) scanning methods are used to gain insights of the protected regions in the body. Brai...
In this study, we developed a lightweight and rapid convolutional neural network (CNN) architecture for chest X-ray images; it primarily consists of a redesigned feature extraction (FE) module and multiscale feature (MF) module and validated using pu...
Medical & biological engineering & computing
Nov 29, 2024
The precise segmentation and three-dimensional reconstruction of the nasopharyngeal airway are crucial for the diagnosis and treatment of adenoid hypertrophy in children. However, traditional methods face challenges such as information loss and low c...
Medical & biological engineering & computing
Nov 29, 2024
Recent advancements in deep learning techniques have significantly improved multi-label chest X-ray (CXR) image classification for clinical diagnosis. However, most previous studies neither effectively learn label correlations nor take full advantage...
Neural networks : the official journal of the International Neural Network Society
Nov 29, 2024
Due to limited photons, low-light environments pose significant challenges for computer vision tasks. Unsupervised domain adaptation offers a potential solution, but struggles with domain misalignment caused by inadequate utilization of features at d...
Journal of applied clinical medical physics
Nov 29, 2024
PURPOSE: Synthetic computed tomography (sCT)-algorithms, which generate computed tomography images from magnetic resonance imaging data, are becoming part of the clinical radiotherapy workflow. The aim of this retrospective study was to evaluate and ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.