A5031089441- Radiomics and Machine Learning in Medical Imaging
- Osteoarthritis Treatment and Mechanisms
- Advanced X-ray and CT Imaging
- Radiation Dose and Imaging
- Sarcoma Diagnosis and Treatment
- Medical Imaging Techniques and Applications
- Knee injuries and reconstruction techniques
- COVID-19 diagnosis using AI
- Artificial Intelligence in Healthcare and Education
- MRI in cancer diagnosis
- Cardiac Imaging and Diagnostics
- Nanoparticle-Based Drug Delivery
- Gastric Cancer Management and Outcomes
- Pancreatic and Hepatic Oncology Research
- Lower Extremity Biomechanics and Pathologies
- Diabetic Foot Ulcer Assessment and Management
- Bone Tumor Diagnosis and Treatments
- Shoulder Injury and Treatment
- Bone and Joint Diseases
- Advanced Image Processing Techniques
- Total Knee Arthroplasty Outcomes
- Medical Imaging and Analysis
- Cancer Genomics and Diagnostics
- Image and Signal Denoising Methods
- Image Processing Techniques and Applications
Tongren Hospital
2019-2025
Shanghai Jiao Tong University
2009-2025
Beijing Tongren Hospital
2022
Shanghai Sixth People's Hospital
2008-2021
Abstract Objective To conduct an overview of meta-analyses radiomics studies assessing their study quality and evidence level. Methods A systematical search was updated via peer-reviewed electronic databases, preprint servers, systematic review protocol registers until 15 November 2022. Systematic reviews with meta-analysis primary were included. Their reporting transparency, methodological quality, risk bias assessed by PRISMA (Preferred Reporting Items for Meta-Analyses) 2020 checklist,...
Abstract This study aims to investigate the influence of adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) on CT radiomics feature robustness. A standardized phantom was scanned under single-energy (SECT) dual-energy (DECT) modes at standard low (20 10 mGy) dose levels. Images SECT 120 kVp corresponding DECT kVp-like virtual monochromatic images were generated with filtered back-projection (FBP), ASIR-V 40% (AV-40) 100% (AV-100) blending...
To evaluate inter- and intra- scan mode scanner repeatability reproducibility of radiomics features within between single-energy CT (SECT) dual-energy (DECT).A standardized phantom with sixteen rods clinical-relevant densities was scanned on seven DECT-capable scanners three SECT-only scanners. The acquisition parameters were selected to present typical abdomen-pelvic examinations the same voxel size. Images SECT at 120 kVp corresponding kVp-like virtual monochromatic images (VMIs) in DECT...
Accurate and effective tumor diagnosis, detection, treatment are key for improving the survival rates of patients. Chimeric antigen receptor T (CAR-T) cell therapy has shown remarkable clinical success in eradicating hematologic malignancies. However, hostile microenvironment solid tumors severely prevents CAR-T cells from migrating infiltrating killing malignant cells. Tumor modulation strategies have attracted much attention field cancer immunotherapy. Multifunctional nanoplatforms that...
Abstract Objective To evaluate whether and how the radiological journals present their policies on use of large language models (LLMs), identify journal characteristic variables that are associated with presence. Methods In this meta-research study, we screened Journals from Radiology, Nuclear Medicine Medical Imaging Category, 2022 Journal Citation Reports, excluding in non-English languages relevant documents unavailable. We assessed LLM policies: (1) policy is present; (2) for authors,...
Abstract Objectives To evaluate robustness of dual-energy CT (DECT) radiomics features virtual unenhanced (VUE) image and monoenergetic (VMI) among different imaging platforms. Methods A phantom with sixteen clinical-relevant densities was scanned on ten DECT platforms comparable scan parameters. Ninety-four radiomic were extracted via Pyradiomics from VUE images VMIs at energy level 70 keV (VMI 70keV ). Test–retest repeatability assessed by Bland–Altman analysis. Inter-platform...
Chest computed tomography (CT) has been found to have high sensitivity in diagnosing novel coronavirus pneumonia (NCP) at the early stage, giving it an advantage over nucleic acid detection during current pandemic. In this study, we aimed develop and validate integrated deep learning framework on chest CT images for automatic of NCP, focusing particularly differentiating NCP from influenza (IP).A total 148 confirmed patients [80 male; median age, 51.5 years; interquartile range (IQR),...
Background: It was difficult to distinguish the cartilage thinning of an entire knee joint and track evolution morphology alongside ages in general population, which great significance for studying osteoarthritis until big imaging data artificial intelligence are fused. The purposes our study (1) explore thickness anatomical regions among a large collection healthy knees, (2) investigate relationship between pattern cartilages increasing ages. Methods: In this retrospective study, 2,481...
To develop and validate a dual-energy computed tomography (DECT) derived radiomics model to predict peritoneal metastasis (PM) in patients with gastric cancer (GC).This retrospective study recruited 239 GC (non-PM = 174, PM 65) histopathological confirmation for status from January 2015 December 2019. All were randomly divided into training cohort (n 160) testing 79). Standardized iodine-uptake (IU) images 120-kV-equivalent mixed (simulating conventional CT images) portal-venous delayed...
Abstract Background Chest CT had high sensitivity in diagnosing novel coronavirus pneumonia (NCP) at early stage, giving it an advantage over nucleic acid detection time of crisis. Deep learning was reported to discover intricate structures from clinical images and achieve expert-level performance medical image analysis. To develop validate integrated deep framework on chest for auto-detection NCP, particularly focusing differentiating NCP influenza (IP). Methods 35 confirmed cases were...
The aim was to determine whether the dual-energy CT radiomics model derived from an iodine map (IM) has incremental diagnostic value for based on 120-kV equivalent mixed images (120 kVp) in preoperative restaging of serosal invasion with locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NAC). A total 155 patients (110 training cohort and 45 testing cohort) LAGC who had standard NAC before surgery were retrospectively enrolled. All analyzed by two radiologists manual...
Studies comparing accuracy of quantification by dual-energy CT (DECT) scanners have been limited small numbers evaluated and narrow ranges scanning conditions.