A5010585047- Osteoarthritis Treatment and Mechanisms
- Medical Imaging and Analysis
- Diabetic Foot Ulcer Assessment and Management
- Infrared Thermography in Medicine
- Human Pose and Action Recognition
- Musculoskeletal pain and rehabilitation
- Rheumatoid Arthritis Research and Therapies
- Digital Imaging for Blood Diseases
- Dementia and Cognitive Impairment Research
- Hand Gesture Recognition Systems
- Semantic Web and Ontologies
- Graphene and Nanomaterials Applications
- Image Processing Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Cognitive Computing and Networks
- Brain Tumor Detection and Classification
- Orthopedic Infections and Treatments
- Biomedical Text Mining and Ontologies
- Pain Mechanisms and Treatments
- Advanced X-ray and CT Imaging
- Retinal Imaging and Analysis
- Total Knee Arthroplasty Outcomes
- Traditional Chinese Medicine Studies
- Cell Image Analysis Techniques
- COVID-19 diagnosis using AI
University of Malaya
2021-2024
Knee osteoarthritis is one of the most common musculoskeletal diseases and usually diagnosed with medical imaging techniques. Conventionally, case identification using plain radiography practiced. However, we acknowledge that knee a 3D complexity; hence, magnetic resonance will be ideal modality to reveal hidden features from three-dimensional view. In this work, feasibility well-known convolutional neural network (CNN) structures (ResNet, DenseNet, VGG, AlexNet) distinguish knees without...
Deep learning, particularly Convolutional Neural Networks, has demonstrated effectiveness in computer-aided diagnosis applications, including knee osteoarthritis analysis. Two of the most common tasks done medical imaging are segmentation and classification tasks. This research investigates feasibility multi-task models for volumetric analysis using Magnetic Resonance Imaging scans diagnosis, while considering computational efficiency. In order to leverage correlation between tasks, two 3D...
Bacterial image analysis plays a vital role in various fields, providing valuable information and insights for studying bacterial structural biology, diagnosing treating infectious diseases caused by pathogenic bacteria, discovering developing drugs that can combat infections,
Alzheimer's disease (AD) is a neurodegenerative ailment that becoming increasingly common, making it major worldwide health concern. Effective care depends on an early and correct diagnosis, but traditional diagnostic techniques are frequently constrained by subjectivity expensive costs. This study proposes novel Vision Transformer-equipped Convolutional Neural Networks (VECNN) uses three-dimensional magnetic resonance imaging to improve diagnosis accuracy. Utilizing the Disease Neuroimaging...
Automated knee segmentation plays an important role in osteoarthritis diagnosis as this disease exhibits different imaging biomarkers it progresses. A good model that is practical and computationally efficient allows a more clinical workflow. This paper presents preliminary study on Depthwise Separable convolutional layers utilizing the end-to-end network, UNet architecture segmentation. Results showed DS2D-UNet DS3D-UNet perform efficiently with adoption of fewer cost computations, without...
Knee osteoarthritis is one of the most common chronic diseases in world. Early detection knee very important because damage joint irreversible at advanced stage. Medical images such as Magnetic Resonance Imaging plays an role diagnosis it provides excellent visualization to OA imaging biomarkers. Current clinical practice relies on manual inspection tedious, especially for 3D volumetric data. The overall aim study develop efficient fully automatic end-to-end automated segmentation multiple...