Colorectal polyps are one of the most direct causes of colorectal cancer. Polypectomy can effectively block the process of colorectal cancer, but accurate polyp segmentation methods are required as an auxiliary means. However, there are several chall...
ACS biomaterials science & engineering
Dec 8, 2024
This study presents an advanced artificial intelligence-driven framework designed to enhance the speed and accuracy of bone fracture detection, addressing key limitations in traditional diagnostic approaches that rely on manual image analysis. The pr...
BACKGROUND: Magnetic resonance imaging (MRI) is a crucial technique for both scientific research and clinical diagnosis. However, noise generated during MR data acquisition degrades image quality, particularly in hyperpolarized (HP) gas MRI. While de...
BACKGROUND: The use of endovascular procedures is becoming increasingly popular across multiple clinical domains. These procedures are generally performed under image guidance using an interventional c-arm x-ray system. Radiation exposure to both pat...
Drowsiness while driving is a major factor contributing to traffic accidents, resulting in reduced cognitive performance and increased risk. This article gives a complete analysis of a real-time, non-intrusive sleepiness detection system based on con...
The prion phenotype in yeast manifests as a white, pink, or red color pigment. Experimental manipulations destabilize prion phenotypes, and allow colonies to exhibit (red) sectored phenotypes within otherwise completely white colonies. Further inve...
Skin cancer is rapidly growing globally. In the past decade, an automated diagnosis system has been developed using image processing and machine learning. The machine learning methods require hand-crafted features, which may affect performance. Recen...
BACKGROUND: Accurate and automatic segmentation of pericardial adipose tissue (PEAT) in cardiac magnetic resonance (MR) images is essential for the diagnosis and treatment of cardiovascular diseases. Precise segmentation is challenging due to high co...
BACKGROUND: Semi-supervised learning provides an effective means to address the challenge of insufficient labeled data in medical image segmentation tasks. However, when a semi-supervised segmentation model is overfitted and exhibits cognitive bias, ...
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