255 citations · 472 across the 11 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…