MRIO: A Magnetic Resonance Imaging Acquisition and Analysis Ontology Magnetic Resonance Imaging (MRI) is a biomedical imaging technology used to non-invasively visualize internal structures of tissues in three-dimensional space. MRI is widely used in studying the structure and function of the human brain and is a powerful tool for diagnosing neurol...
Gender Differences in Acute Axonal Pathology Following Experimental Concussion Academic Background Each year, approximately 50 million people worldwide suffer from concussions, also known as mild traumatic brain injuries (TBI). However, for more than 15% of patients, this “mild” brain injury can lead to lasting neurocognitive dysfunction. The exist...
Neurohackademy: Combining Online and Offline Neurological Informatics Education Background Introduction In recent years, human neuroscience has entered an era of big data. Due to initiatives like the Human Connectome Project and the Adolescent Brain Cognitive Development (ABCD) study, scientists have acquired datasets of previously unimaginable sca...
Broadband Achromatic Spatial Differential Imaging with Optical Spin-Orbit Coupling Background Introduction In image processing, traditional spatial differentiation is typically accomplished through digital electronic computation. However, many big data applications require real-time and high-throughput image processing, which poses a tremendous cha...
In contemporary clinical oncology practice and drug development, the methods for evaluating tumor response are on the cusp of a revolution. Since the World Health Organization (WHO) proposed tumor response classification criteria for assessing the effectiveness of anti-cancer drugs in 1981, this field has undergone several improvements. Notably, th...
Background of Urgent Problem Prostate cancer is one of the most common cancers among men. Metastatic castration-resistant prostate cancer (mCRPC) is an advanced form of prostate cancer characterized by resistance to castration therapy. Radium-223 is an α-emitting radiopharmaceutical that has been shown to improve overall survival (OS) and reduce sk...
Study on the Role of Machine Learning-Assisted Quantitative Hyperspectral Imaging in Brain Tumor Resection Background Introduction Complete resection of malignant gliomas has always been challenged by the difficulty of distinguishing tumor cells in invasive regions. The background of this study is: In neurosurgery, the application of 5-aminolevulin...
Breakthrough in Automated Echocardiogram Diagnosis via Deep Learning: A Comparative Study of Self-Supervised Learning Methods Research Background With the rapid development of artificial intelligence and machine learning technologies, their role in medical imaging diagnosis is becoming increasingly significant. In particular, Self-Supervised Learni...
Precision Imaging of Cardiac Function and Infarct Scar Size: A Study with Ultrahigh-Field MRI in Acute and Chronic Porcine Models of Myocardial Infarction Research Background Cardiac magnetic resonance imaging (MRI) is an accurate and highly reproducible technique for assessing cardiac function and volume. In recent years, ultrahigh-field (UHF) MRI...
Improved Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning Background Introduction The segmentation of pediatric brain tumors is a critical task in tumor volume analysis and artificial intelligence algorithms. However, this process is time-consuming and requires the expertise of neuroradiologists. Although significant research ...