A5067294689- Cerebrovascular and Carotid Artery Diseases
- Radiomics and Machine Learning in Medical Imaging
- Acute Ischemic Stroke Management
- Cerebrovascular and genetic disorders
- Head and Neck Cancer Studies
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Photoacoustic and Ultrasonic Imaging
- Lung Cancer Diagnosis and Treatment
- Bone fractures and treatments
- Nanoplatforms for cancer theranostics
- Inhalation and Respiratory Drug Delivery
- Ultrasound and Hyperthermia Applications
- Imbalanced Data Classification Techniques
- Immune cells in cancer
- Fuzzy Logic and Control Systems
- Oral health in cancer treatment
- Advanced Radiotherapy Techniques
- Artificial Intelligence in Healthcare
- Molecular Sensors and Ion Detection
- Cardiovascular Health and Disease Prevention
- Respiratory Support and Mechanisms
- Biomarkers in Disease Mechanisms
- Advanced X-ray and CT Imaging
- Luminescence and Fluorescent Materials
- MRI in cancer diagnosis
Hong Kong Polytechnic University
2023-2025
Guangzhou Regenerative Medicine and Health Guangdong Laboratory
2020
Southern Medical University
2019
Nanfang Hospital
2019
Interpretable artificial intelligence (AI), also known as explainable AI, is indispensable in establishing trustable AI for bench-to-bedside translation, with substantial implications human well-being. However, the majority of existing research this area has centered on designing complex and sophisticated methods, regardless their interpretability. Consequently, main prerequisite implementing trustworthy medical domains not been met. Scientists have developed various explanation methods...
Background: Pulmonary segments are valuable because they can provide more precise localization and intricate details of lung cancer than lobes. With advances in precision therapy, there is an increasing demand for the identification visualization pulmonary computed tomography (CT) images to aid treatment cancer. This study aimed integrate multiple deep-learning models accurately segment CT using a bronchial tree (BT)-based approach. Methods: The proposed segmentation method BT-based approach...
Objective.This study aimed to propose a method for obtaining anatomy-wise lung ventilation image (VIaw) that enables functional assessment of parenchyma and tumor-blocked pulmonary segments. The VIawwas used define multiple volumes the thereby support radiation treatment planning.Approach.A super-voxel-based was employed generate VIsvd. In VIsvdof 11 patients with tumor blockage airway, value in segments set 0 VIaw. divided into regions high volume (HFV), unrecoverable low (LFV), recoverable...
(1) Background: Acute oral mucositis is the most common side effect for nasopharyngeal carcinoma patients receiving radiotherapy. Improper or delayed intervention to severe AOM could degrade quality of life survival NPC patients. An effective prediction method needed individualized management in era personalized medicine. (2) Methods: A total 242 biopsy-proven were retrospectively recruited this study. Radiomics features extracted from contrast-enhanced CT (CECT), T1-weighted (cT1WI), and...
Despite reported correlations between intracranial arterial calcification (IAC) and white matter hyperintensities (WMH), little is known about the relationship IAC pattern WMH. By differentiating intimal medial IAC, we aimed to investigate WMH.Consecutive acute stroke patients were included. was categorized as or on plain brain CT. The number of cerebral arteries involved by for each patient recorded. severity defined focal diffuse. On MRI, burden WMH visually graded classified absent mild,...
Abstract Background Despite previously reported correlations between intracranial arterial calcification (IAC) and white matter hyperintensities (WMH), little is known about the relationship IAC pattern WMH. By differentiating intimal medical IAC, we aimed to investigate Methods Consecutive patients with acute ischemic stroke were included. was categorized as or medial on plain brain CT. The number of cerebral arteries involved by for each patient recorded. severity artery defined focal...
This study aims to evaluate the repeatability of radiomics and dosiomics features via image perturbation patients with cervical cancer. A total 304 cancer planning CT images dose maps were retrospectively included. Random translation, rotation, contour randomization applied before feature extraction. The was assessed using intra-class correlation coefficient (ICC). Pearson (r) adopted quantify between characteristics repeatability. In general, lower compared features, especially after...