255 citations · 472 across the 11 of their papers we have counts for
11 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…
Improving 360 Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised Learning
Ilwi Yun, Hyuk-Jae Lee, Chae Eun Rhee
Due to difficulties in acquiring ground truth depth of equirectangular (360) images, the quality and quantity of equirectangular depth data today is insufficient to represent the v…
The CNN-based Coronary Occlusion Site Localization with Effective Preprocessing Method
YeongHyeon Park, Il Dong Yun, Si-Hyuck Kang
The Coronary Artery Occlusion (CAO) acutely comes to human, and it highly threats the human's life. When CAO detected, Percutaneous Coronary Intervention (PCI) should be conducted…
Reinforcing Medical Image Classifier to Improve Generalization on Small Datasets
Walid Abdullah Al, Il Dong Yun
With the advents of deep learning, improved image classification with complex discriminative models has been made possible. However, such deep models with increased complexity requ…
Reinforcement Learning-based Automatic Diagnosis of Acute Appendicitis in Abdominal CT
Walid Abdullah Al, Il Dong Yun, Kyong Joon Lee
Acute appendicitis characterized by a painful inflammation of the vermiform appendix is one of the most common surgical emergencies. Localizing the appendix is challenging due to i…
Centerline Depth World Reinforcement Learning-based Left Atrial Appendage Orifice Localization
Walid Abdullah Al, Il Dong Yun, Eun Ju Chun
Left atrial appendage (LAA) closure (LAAC) is a minimally invasive implant-based method to prevent cardiovascular stroke in patients with non-valvular atrial fibrillation. Assessin…
Learning Bone Suppression from Dual Energy Chest X-rays using Adversarial Networks
Dong Yul Oh, Il Dong Yun
Suppressing bones on chest X-rays such as ribs and clavicle is often expected to improve pathologies classification. These bones can interfere with a broad range of diagnostic task…
Comparison of RNN Encoder-Decoder Models for Anomaly Detection
YeongHyeon Park, Il Dong Yun
In this paper, we compare different types of Recurrent Neural Network (RNN) Encoder-Decoders in anomaly detection viewpoint. We focused on finding the model that can learn the same…
Partial Policy-based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images
Walid Abdullah Al, Il Dong Yun
Deploying the idea of long-term cumulative return, reinforcement learning has shown remarkable performance in various fields. We propose a formulation of the landmark localization…
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…
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…