2 citations · 3 across the 6 of their papers we have counts for
6 papers
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…
Detecting Pulmonary Embolism from Computed Tomography Using Convolutional Neural Network
Chia-Hung Yang, Yun-Chien Cheng, Chin Kuo
The clinical symptoms of pulmonary embolism (PE) are very diverse and non-specific, which makes it difficult to diagnose. In addition, pulmonary embolism has multiple triggers and…
Computerized Tomography Pulmonary Angiography Image Simulation using Cycle Generative Adversarial Network from Chest CT imaging in Pulmonary Embolism Patients
Chia-Hung Yang, Yun-Chien Cheng, Chin Kuo
The purpose of this research is to develop a system that generates simulated computed tomography pulmonary angiography (CTPA) images clinically for pulmonary embolism diagnoses. No…
Feature-enhanced Adversarial Semi-supervised Semantic Segmentation Network for Pulmonary Embolism Annotation
Ting-Wei Cheng, Jerry Chang, Ching-Chun Huang +2
This study established a feature-enhanced adversarial semi-supervised semantic segmentation model to automatically annotate pulmonary embolism lesion areas in computed tomography p…
Convolutional Neural Network for Early Pulmonary Embolism Detection via Computed Tomography Pulmonary Angiography
Ching-Yuan Yu, Ming-Che Chang, Yun-Chien Cheng +1
This study was conducted to develop a computer-aided detection (CAD) system for triaging patients with pulmonary embolism (PE). The purpose of the system was to reduce the death ra…
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…