2 citations · 3 across the 4 of their papers we have counts for
4 papers
Using Few-Shot Learning to Classify Primary Lung Cancer and Other Malignancy with Lung Metastasis in Cytological Imaging via Endobronchial Ultrasound Procedures
Ching-Kai Lin, Di-Chun Wei, Yun-Chien Cheng
This study presents a computer-aided diagnosis (CAD) system to assist early detection of lung metastases during endobronchial ultrasound (EBUS) procedures, significantly reducing f…
Towards Enhanced Analysis of Lung Cancer Lesions in EBUS-TBNA -- A Semi-Supervised Video Object Detection Method
Jyun-An Lin, Yun-Chien Cheng, Ching-Kai Lin
This study aims to establish a computer-aided diagnostic system for lung lesions using endobronchial ultrasound (EBUS) to assist physicians in identifying lesion areas. During EBUS…
Using Spatio-Temporal Dual-Stream Network with Self-Supervised Learning for Lung Tumor Classification on Radial Probe Endobronchial Ultrasound Video
Ching-Kai Lin, Chin-Wen Chen, Yun-Chien Cheng
The purpose of this study is to develop a computer-aided diagnosis system for classifying benign and malignant lung lesions, and to assist physicians in real-time analysis of radia…
The interpretation of endobronchial ultrasound image using 3D convolutional neural network for differentiating malignant and benign mediastinal lesions
Ching-Kai Lin, Shao-Hua Wu, Jerry Chang +1
The purpose of this study is to differentiate malignant and benign mediastinal lesions by using the three-dimensional convolutional neural network through the endobronchial ultraso…