20 citations · 20 across the 1 of their papers we have counts for
4 papers
Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization
Seung Yeon Shin, Soochahn Lee, Kyoung Jin Noh +2
We present a method to extract coronary vessels from fluoroscopic x-ray sequences. Given the vessel structure for the source frame, vessel correspondence candidates in the subseque…
Deep Vessel Segmentation By Learning Graphical Connectivity
Seung Yeon Shin, Soochahn Lee, Il Dong Yun +1
We propose a novel deep-learning-based system for vessel segmentation. Existing methods using CNNs have mostly relied on local appearances learned on the regular image grid, withou…
Scale Space Approximation in Convolutional Neural Networks for Retinal Vessel Segmentation
Kyoung Jin Noh, Sang Jun Park, Soochahn Lee
Retinal images have the highest resolution and clarity among medical images. Thus, vessel analysis in retinal images may facilitate early diagnosis and treatment of many chronic di…
Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images
Seung Yeon Shin, Soochahn Lee, Il Dong Yun +2
We propose a framework for localization and classification of masses in breast ultrasound (BUS) images. We have experimentally found that training convolutional neural network base…