A5068920925- Optical Coherence Tomography Applications
- Photoacoustic and Ultrasonic Imaging
- Spectroscopy Techniques in Biomedical and Chemical Research
- Glioma Diagnosis and Treatment
- Advanced Fluorescence Microscopy Techniques
- Optical Imaging and Spectroscopy Techniques
- Dental Radiography and Imaging
- CNS Lymphoma Diagnosis and Treatment
- Cultural Heritage Materials Analysis
- Oral microbiology and periodontitis research
- Optical Polarization and Ellipsometry
National Yang Ming Chiao Tung University
2019-2024
Complete removal of brain tumor is the most interest to a surgeon because resection area directly relates recurrence rate. Although there are many biomedical imaging modalities applied locate positions tumors, they lack spatial resolution precisely delineate boundary between and normal tissues also inconvenient be used intraoperatively. This study aims examine feasibility label-free, polarization-sensitive optical coherence tomography (PS-OCT) for distinguishing tumors from tissues. Ex vivo...
In neurosurgery, accurately identifying brain tumor tissue is vital for reducing recurrence. Current imaging techniques have limitations, prompting the exploration of alternative methods. This study validated a binary hierarchical classification tissues: normal tissue, primary central nervous system lymphoma (PCNSL), high-grade glioma (HGG), and low-grade (LGG) using transfer learning. Tumor specimens were measured with optical coherence tomography (OCT), MobileNetV2 pre-trained model was...
Abstract During the treatment of periodontitis, removal dental calculus is essential but still tricky despite developments several imaging modalities. In this research, we propose a novel approach to provide an intuitive guidance, automatically detect present subgingival calculus, and identify site lesion in optical coherence tomography images based on convolutional neural network model class activation maps technique. Our result shows good visualizations both B‐scan volumetric view. We...
Dental enamel constitutes the outer layer of a crown teeth and grows nearly parallel. This unique nanostructure makes possess birefringence properties. Currently, there is still no appropriate clinical solution to examine dental hard tissue diseases. Therefore, we developed an optical polarization imaging system for diagnosing calculus, caries, cracked tooth syndrome. By obtaining Stokes signals reflected from samples, Mueller images were constructed analyzed using Lu-Chipman decomposition....
Significance: Differentiation of primary central nervous system lymphoma from glioblastoma is clinically crucial to minimize the risk treatments, but current imaging modalities often misclassify and lymphoma. Therefore, there a need for methods achieve high differentiation power intraoperatively. Aim: The aim develop corroborate method classifying normal brain tissue, glioblastoma, using optical coherence tomography with deep learning algorithm in an ex vivo experimental design. Approach: We...
Abstract The delineation of brain tumor margins has been a challenging objective in neurosurgery for decades. Despite the development various preoperative imaging techniques, current methodology is still insufficient clinical practice. We present an intraoperative optical intrinsic signal system surgery and establish data processing procedure model to localize tumors. From experimental result glioblastoma patient, we observe relative small oscillation ΔHbD region speculate that vessels have...
Background: Instant histological diagnosis is an important procedure during surgery for histology-unknown lung tumors. Through such a brief diagnosis, accurate decision-making excision of the target, especially in cancer, crucial cure disease. There still limited advancement this kind microscopic diagnostic technology these years.Methods: We design spectral domain optical coherence tomography (SD-OCT) system and perform real-time scanning targeting tumor intraoperatively. The images got from...
In this study, we combined optical technology and machine learning to classify dental problems.We took totally 16 samples 79 OCT images including 32 calculus(CA) 47 normal (HC) images. After image processing, obtained attenuation coefficient, surface roughness spectral information, put these features into two layer neural networks for training. We divided the data training (24 CA / 37 HC = 61 total) test (8 10 18 data, was checked with 10-fold cross validation confirm no over-trained. The...