A5005644733- Radiomics and Machine Learning in Medical Imaging
- Lung Cancer Diagnosis and Treatment
- Advanced Neuroimaging Techniques and Applications
- MRI in cancer diagnosis
- Sarcoma Diagnosis and Treatment
- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
- Salivary Gland Tumors Diagnosis and Treatment
- Histiocytic Disorders and Treatments
- Trigeminal Neuralgia and Treatments
- Ovarian function and disorders
- Medical Imaging and Analysis
- Obsessive-Compulsive Spectrum Disorders
- Oral and Maxillofacial Pathology
- Head and Neck Cancer Studies
- Polyomavirus and related diseases
- Advanced X-ray and CT Imaging
- COVID-19 Clinical Research Studies
- AI in cancer detection
- Viral-associated cancers and disorders
- Sulfur-Based Synthesis Techniques
- Lymphoma Diagnosis and Treatment
- Neurosurgical Procedures and Complications
- COVID-19 diagnosis using AI
- Fluorine in Organic Chemistry
Taizhou Municipal Hospital
2009-2024
Taizhou University
2010-2024
University of Zulia
2023
Nanjing Medical University
2023
Jiangsu Province Hospital
2023
Second Affiliated Hospital of Zhejiang University
2022
Shanghai Medical College of Fudan University
2021-2022
Fudan University Shanghai Cancer Center
2020-2022
Hunan University of Science and Engineering
2022
For stage-I lung adenocarcinoma, the 5-year disease-free survival (DFS) rates of non-invasive adenocarcinoma (non-IA) is different with invasive (IA). This study aims to develop CT image based artificial intelligence (AI) schemes classify between non-IA and IA nodules, incorporate deep learning (DL) radiomics features improve classification performance. We collect 373 surgical pathological confirmed ground-glass nodules (GGNs) from 323 patients in two centers. It involves 205 (including 107...
To study the rules that apparent diffusion coefficient (ADC) changes with time and space in cerebral infarction, to provide evidence defining infarction stages. 117 work-ups 98 patients (12 hyperacute, 43 acute, 29 subacute, 10 steady, 23 chronic infarctions) were imaged both conventional MRI weighted imaging. The average ADC values, relative (rADC) values or rADC from center periphery of lesion calculated. hyperacute acute depressed obviously. stage was minimized, increased progressively as...
Salivary gland tumors are a rare, histologically heterogeneous group of tumors. The distinction between malignant and benign the parotid is clinically important. This study aims to develop evaluate deep-learning network for diagnosing via deep learning MR images.Two hundred thirty-three patients with were enrolled in this study. Histology results available all All underwent MRI scans, including T1-weighted, CE-T1-weighted T2-weighted imaging series. glands segmented on three image series by...
Visible-light photocatalytic trifluoromethylselenolation of ortho -hydroxyarylenaminones is reported, which provides a green protocol for the efficient and rapid synthesis trifluoromethylselenylated chromones.
This study aims to develop a deep neural network (DNN)-based two-stage risk stratification model for early lung adenocarcinomas in CT images, and investigate the performance compared with practicing radiologists. A total of 2393 GGNs were retrospectively collected from 2105 patients four centers. All pathologic results obtained surgically resected specimens. was developed based on 3D residual atrous convolution module diagnose benign malignant (Task1) classify between invasive adenocarcinoma...
The purpose of the study was to evaluate value high-resolution three-dimensional fast low angle shot (3D-FLASH) and constructive interference in steady-state (3D-CISS) MRI sequence solely or combination both visualization neurovascular relationship patients with trigeminal neuralgia (TN).65 unilateral TN underwent 3D-FLASH 3D-CISS imaging were retrospectively studied. Neurovascular at intracisternal segment nerve reviewed by two experienced neuroradiologist, who blinded clinical details....
This study aims to develop a CT-based hybrid deep learning network predict pathological subtypes of early-stage lung adenocarcinoma by integrating residual (ResNet) with Vision Transformer (ViT). A total 1411 pathologically confirmed ground-glass nodules (GGNs) retrospectively collected from two centers were used as internal and external validation sets for model development. 3D ResNet ViT applied investigate frameworks classify three namely invasive (IAC), minimally in situ, respectively....
To evaluate the prognostic value of baseline SUVmax F-FDG PET-CT in extranodal natural killer/T-cell lymphoma (NKTCL) patients.From January 2010 to December 2015, 141 NKTCL patients with staging scan were divided into two group based on cutoff obtained from operating characteristic (ROC) curves. All received radiotherapy, chemotherapy or chemoradiation. Survival analysis was performed basis SUVmax.The median tumors 11.67 (range 2.6-34.6). The ROC curves showed that optimal 9.65. groups: low...
Abstract To investigate the characteristics of diffusion tensor imaging (DTI) central nervous system in children with Tourette syndrome (TS). Fifteen TS (TS group) and 15 normal (control were studied, all them underwent DTI. The apparent coefficient (ADC) fractional anisotropy (FA) parameters calculated using DTIStudio software. region interest was delineated manually. ADC FA values bilateral caudate nucleus, globus pallidus, putamen, thalamus, frontal lobe white matter measured editor...
A parotid neoplasm is an uncommon condition that only accounts for less than 3% of all head and neck cancers, they make up 0.3% new cancers diagnosed annually. Due to their nonspecific imaging features heterogeneous nature, accurate preoperative diagnosis remains a challenge. Automatic tumor segmentation may help physicians evaluate these tumors. Two hundred eighty-five patients with benign or malignant tumors were enrolled in this study. Parotid tissues segmented by 3 radiologists on...
Background: Regarding the outbreak of highly contagious 2019 Novel Coronavirus (2019-nCoV) in various countries and regions, data have been needed on early chest CT images clinical characteristics affected patients. Objectives: To explore computed tomography (CT) Disease (COVID-19) patients to improve diagnostic level this respiratory disease. Methods: An analysis retrospectively was implemented radiological features 12 with COVID-19 who had undergone scanning designated hospital from Jan...
Objective To summarize the radiological features of follicular dendritic cell tumor spleen (FDCS). Methods The clinical, and pathological data 8 patients from November 2011 to 2017 in 5 hospitals with FDCS confirmed by pathology were retrospectively analyzed. All underwent CT examinations including plan enhanced CT. Three additional MRI two PET-CT simultaneously. The imaging such as location, number, shape, boundary, size, internal structure, density (or signal, 18F-fluorodeoxyglucose...
Objective To study the values of apparent diffusion coefficient (ADC) changing with time and space in cerebral infarction,and to provide evidence defining infarction stages.Methods 117 work-ups 98 patients (12 hyperacute,43 acute,29 subacute,10 steady,and 23 chronic infarctions) were imaged both conventional MRI weighted imaging.The average ADC values,the relative (rADC) values,and or rADC from center periphery lesion calculated.Results The hyperacute acute depressed obviously.rADC stage was...
Abstract. Early diagnosis and treatment are vital to improving lung cancer patients’ quality of life survival rate. This study aimed investigate the value dynamic enhanced scanning examination by computed tomography (CT) in early diagnosis. One hundred twenty patients with isolated nodules were selected analyze this diagnostic method, using pathological results as gold standard. Of 120 pa-tients pulmonary nodules, was confirmed patho-logical 96 (adenocarcinoma lung) 24 benign lesions. The...