A5004203471- Osteoarthritis Treatment and Mechanisms
- Total Knee Arthroplasty Outcomes
- Orthopedic Surgery and Rehabilitation
- Orthopedic Infections and Treatments
- Medical Imaging and Analysis
- Hip disorders and treatments
- Cancer-related molecular mechanisms research
- Bone and Joint Diseases
- Knee injuries and reconstruction techniques
- Bone Tissue Engineering Materials
- Dental materials and restorations
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- Rheumatoid Arthritis Research and Therapies
- Dental Implant Techniques and Outcomes
- Inflammatory mediators and NSAID effects
- Shoulder Injury and Treatment
- Sports injuries and prevention
- Integrated Circuits and Semiconductor Failure Analysis
- Extracellular vesicles in disease
- Advanced Computing and Algorithms
- Pharmacological Effects of Natural Compounds
- Brain Tumor Detection and Classification
- Orthopaedic implants and arthroplasty
- Medicinal plant effects and applications
Harbin Medical University
2015-2025
Second Affiliated Hospital of Harbin Medical University
2015-2025
Knee segmentation and landmark localization from 3D MRI are two significant tasks for diagnosis treatment of knee diseases. With the development deep learning, Convolutional Neural Network (CNN) based methods have become mainstream. However, existing CNN mostly single-task methods. Due to complex structure bone, cartilage ligament in knee, it is challenging complete or alone. And establishing independent models all will bring difficulties surgeon's clinical using. In this paper, a Spatial...
Background Knee cartilage is the most crucial structure in knee, and reduction of thickness a significant factor occurrence development osteoarthritis. Measuring allows for more accurate assessment wear, but this process relatively time-consuming. Our objectives encompass using various DL methods to segment knee from MRIs taken with different equipment parameters, building DL-based model measuring grading cartilage, establishing standardized database thickness. Methods In retrospective...
Because the pathophysiology of osteoarthritis (OA) has not been fully elucidated, targeted treatments are lacking. In this study, we assessed role and underlying mechanism apolipoprotein D (APOD) on development OA.
The progression of knee osteoarthritis is mainly characterized by the reduction in joint space width (JSW). goal this study was to build a segmentation model through deep learning (DL) methods and develop for automatically measuring JSW. Furthermore, we predicted JSW changes sixth year based on regression models. data sourced from Osteoarthritis Initiative database. We filtered X-ray images 1,947 participants tested six neural networks an automatic measurement model. Subsequently, combined...
The objective of this study is to develop a novel automatic convolutional neural network (CNN) that aids in the diagnosis meniscus injury, while enabling visualization lesion characteristics. This will improve accuracy and reduce times.We presented cascaded-progressive (C-PCNN) method for diagnosing injuries using magnetic resonance imaging (MRI). A total 1396 images collected hospital were used training testing. testing was 5-fold cross validation. Using intraoperative arthroscopic MRI as...
Abstract Background To develop a fully automated CNN detection system based on magnetic resonance imaging (MRI) for ACL injury, and to explore the feasibility of injury MRI images. Methods Including 313 patients aged 16 – 65 years old, raw data are 368 pieces with injured 100 intact ACL. By adding flipping, rotation, scaling other methods expand data, final set is 630 including 355 275 Using proposed model two attention mechanism modules, sets trained tested fivefold cross-validation....
The incidence of osteonecrosis the femoral head (ONFH) is increasing gradually, rapid and accurate grading ONFH critical. existing Steinberg staging criteria grades according to proportion necrosis area area.In clinical practice, region are mainly estimated by observation experience doctor. This paper proposes a two-stage segmentation framework, which can be used segment necrosis, as well diagnosis.The core proposed framework multiscale geometric embedded convolutional neural network...
Abstract Introduction The Steinberg classification system is commonly used by orthopedic surgeons to stage the severity of patients with osteonecrosis femoral head (ONFH), and it includes mild, moderate, severe grading each based on area affected. However, clinicians mostly grade approximately visual assessment or not at all. To accurately distinguish early ONFH, we propose a convolutional neural network (CNN) magnetic resonance imaging (MRI) hip joint aid diagnosis ONFH. Materials Methods...
A nano-sized hydroxyapatite/zirconia (3 mol-% yttria-stabilised cubic zirconia) bioceramic was fabricated by a hot pressure sintering process in this study. The vitro biocompatibility of researched, with the aim validating effects incisions bodies 4-month-old rats made hydroxyapatite–yttria-stabilised zirconia scalpel, and to illustrate incision properties tissues. wound-healing experiment nano knife studied, subcutaneous tissues musculature samples were obtained analysed optical microscopy...
Prosthesis loosening after THA is a rather common complication. For DDH patients with Crowe IV, the surgical risk and complexity significant. S-ROM prosthesis combined subtrochanteric osteotomy treatment. However, of modular femoral (S-rom) uncommon in has very low incidence. With prostheses distal looseness are rarely reported. Non-union complication osteotomy. We report three IV who developed following an addressed management these as likely underlying causes.