A5028566757- Advanced Neuroimaging Techniques and Applications
- Genetic Neurodegenerative Diseases
- Mitochondrial Function and Pathology
- Neurological and metabolic disorders
- MRI in cancer diagnosis
- Renal cell carcinoma treatment
- Stroke Rehabilitation and Recovery
- Parkinson's Disease Mechanisms and Treatments
- Radiomics and Machine Learning in Medical Imaging
- Transcranial Magnetic Stimulation Studies
- Motor Control and Adaptation
Fujian Medical University
2021-2025
First Affiliated Hospital of Fujian Medical University
2021-2025
To develop a machine learning (ML)-based classifier for discriminating between low-grade (ISUP I-II) and high-grade III-IV) clear cell renal carcinomas (ccRCCs) using MRI textures.We retrospectively evaluated total of 99 patients (with 61 38 ccRCCs), who were randomly divided into training set (n = 70) validation 29). Regions interest (ROIs) all tumors manually drawn three times by radiologist at the maximum lesion level cross-sectional CMP sequence images. The quantitative texture analysis...
The analysis of structural covariance has emerged as a powerful tool to explore the morphometric correlations among broadly distributed brain regions. However, little is known about interactions between damaged primary motor cortex (M1) and other regions in stroke patients with deficits. This study aimed at investigating pattern ipsilesional M1 chronic subcortical High-resolution T1-weighted images were acquired from 58 deficits (29 left-sided lesions 29 right-sided lesions) 50 healthy...
Abstract Objectives Spinocerebellar ataxia type 3 is a disorder within the brain network. However, relationship between network and disease severity still unclear. This study aims to investigate changes in white matter (WM) structural motor network, both preclinical ataxic stages, its with severity. Methods For this study, 20 ataxic, SCA3 patients, healthy controls were recruited received MRI scans. Disease was quantified using SARA ICARS scores. The WM created probabilistic fiber tracking...