Featured Projects

Featured Projects

Selected research systems bridging clinical need and AI method.

active

AI-assisted Vocal Fold Disease Analysis

Deep learning models for classification, detection, and segmentation of vocal fold lesions from flexible laryngoscopy images.

Lead researcher

PyTorchComputer VisionSegmentationClassification
published

Laryngoscopy Image Analysis & VoFoCD Dataset

Medical AI research for improving laryngoscopy image classification by integrating global information and local features.

First author

Deep LearningDataset ConstructionPyTorch
active

Head and Neck CT Lesion Segmentation

Segmentation-guided analysis of abscess, tumor, and cyst lesions in head-and-neck CT images.

Lead researcher

MONAInnU-Net3D Segmentation
published

Content-Based Retrieval of Head and Neck CT Images

A medical image retrieval framework using segmentation, radiomics, and deep imaging features.

First author

RadiomicsCBIRFeature Learning
active

Explainable AI & Radiomics for Age-Associated Lesion Phenotyping

A research direction combining segmentation-guided radiomics and deep features to predict chronological age and identify imaging phenotypes in head-and-neck CT lesions.

Lead researcher

Explainable AIRadiomicsDeep Features
active

Mobile AI for ENT Screening

Lightweight AI models for real-time or near-real-time support in ENT endoscopy and vocal fold assessment.

Lead researcher

Edge AIModel CompressionMobile