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ISSN: 2950-1628

Developmental Trends in Corpus Callosum Thickness Among Preschool Children

The corpus callosum plays a crucial role in integrated brain functions, and its development in childhood is strongly associated with subsequent cognitive, emotional, and behavioral development. However,...

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Unbiasing fairness evaluation of radiology AI model

Fairness of artificial intelligence and machine learning models, often caused by imbalanced datasets, has long been a concern. While many efforts aim to minimize model bias, this study suggests that...

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Radio-immunomics in hepatocellular carcinoma: Unraveling the tumor immune microenvironment

Hepatocellular carcinoma (HCC) ranks as the sixth most prevalent and the fourth most lethal malignancy worldwide, frequently manifesting at advanced stages with limited therapeutic options. Despite...

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Myocardial viability under various ischemic burdens in chronic total occlusions: A stress-cardiac magnetic resonance study

This study aimed to analyze each myocardial segment's ischemic burden, scarring, function, and viability by late gadolinium enhancement (LGE) imaging and stress-MRI using adenosine....

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Allen Human Brain Atlas and magnetic resonance imaging in schizophrenia

Schizophrenia is among top disability causes worldwide; however, its pathological mechanism is still unclear. In order to advance the research progress on schizophrenia, the Schizophrenia Imaging Lab...

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Radiomics model of CTE can detect inflammatory activity in intestinal Crohn's disease

To investigate the diagnostic value of a computed tomography enterography (CTE)-based radiomics model (RM) in the detection of active inflamXGmation in patients with intestinal Crohn's disease (CD)...

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7T MRI in cerebrovascular disorders: From large artery abnormalities to small vessel disease

There is a growing interest and adoption of 7 Tesla (T) magnetic resonance imaging (MRI) in the field of medicine and research. In the domain of neuroimaging, 7T MRI shows notable advantages over lower...

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Thoracic CT imaging in obesity: Technical challenges, imaging findings and future outlook

Obesity is a highly prevalent and increasing global medical problem. It is expected that most radiologists will come across computed tomography studies of obese patients in their daily work. Obesity...

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Evaluation of cerebellar aging in MRI images: Fractal analysis compared to Euclidean geometry-based morphometry

This study aimed to identify age-related changes in the fractal dimensions of the cerebellum and compare the sensitivity of fractal analysis and conventional Euclidean geometry-based morphometry to...

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Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports

Medical images and radiology reports are essential for physicians to diagnose medical conditions. However, the vast diversity and cross-source heterogeneity inherent in these data have posed significant...

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Cardiovascular Medical Image and Analysis based on 3D Vision: A Comprehensive Survey

With the rapid development of 3D vision and computer graphics technology, the way humans interact with the world has undergone significant transformations. 3D vision-related technologies have profoundly...

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A Systematic Evaluation of GPT-4V’s Multimodal Capability for Chest X-ray Image Analysis

This work evaluates GPT-4V’s multimodal capability for medical image analysis, focusing on three representative tasks radiology report generation, medical visual question answering, and medical visual...

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Opportunities and challenges in the application of large artificial intelligence models in radiology

Influenced by ChatGPT, artificial intelligence (AI) large models have witnessed a global upsurge in large model research and development. As people enjoy the convenience by this AI large model, more...

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The general intelligence of GPT–4, its knowledge diffusive and societal influences, and its governance

Recent breakthroughs in artificial intelligence (AI) research include advancements in natural language processing (NLP) achieved by large language models (LLMs), and; in particular, generative pre–trained...

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Review and prospects of new progress in intelligent imaging research on lymph node metastasis in esophageal carcinoma

Esophagus carcinoma (EC) ranks sixth in cancer-related mortality and seventh in terms of morbidity worldwide, and radical esophagectomy is considered as the basis of comprehensive treatment for locally...

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MCFCN: Multi-scale capsule-weighted fusion classification network for lung disease classification based on chest CT scans

This paper aims to propose a Multi-scale Capsule-weighted Fusion Classification Network (MCFCN), a classification model for automatic diagnosis of lung lesions by CT scanning....

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Deep learning-based artificial intelligence for assisting diagnosis, assessment and treatment in soft tissue sarcomas

Soft tissue sarcomas (STSs) represent a group of heterogeneous mesenchymal tumors of which are generally classified as per the histopathology. Despite being rare in incidence and prevalence, STSs are...

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A survey of emerging applications of diffusion probabilistic models in MRI

Diffusion probabilistic models (DPMs) which employ explicit likelihood characterization and a gradual sampling process to synthesize data, have gained increasing research interest. Despite their huge...

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Defining a radiomics feature selection method for predicting response to transarterial chemoembolization in hepatocellular carcinoma patients

To assess the utility of different radiomics feature selection methods in predicting transarterial chemoembolization (TACE) response in hepatocellular carcinoma (HCC) patients....

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Lung cancer screening, diagnosis, and treatment: The radiologist's perspective

The epidemiological of lung cancer surgery patients is changing, resulting in changes in diagnosis and treatment. Changing the way and content of imaging reports in response to the above changes is...

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Magnetic resonance-guided focused ultrasound in intracranial diseases: Clinical applications and future directions

Magnetic resonance-guided focused ultrasound (MRgFUS) is a non-invasive technique for neuroregulation that offers several advantages, including non-invasiveness, no need for general anesthesia requirement,...

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Research and application progress of radiomics in neurodegenerative diseases

Neurodegenerative diseases refer to degenerative diseases of the nervous system caused by neuronal degeneration and apoptosis. Usually, the onset of the disease is insidious, and the progression is...

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Ferroptosis, M6A and immune checkpoint-related gene expression in the middle temporal gyrus of the Alzheimer's disease brain

Alzheimer's disease (AD) is a common genetically related cognitive disorder. Studies have shown that ferroptosis, N⁶-Methyladenosine (M6A) and immune checkpoint are related to the development of AD....

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Metabolite changes and impact factors in mild traumatic brain injury patients: A review on magnetic resonance spectroscopy

The high incidence of mild traumatic brain injury (mTBI) and the associated post-concussion symptoms, such as headache and cognitive deficits, have captured the significant attention from researchers...

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