75 citations · 136 across the 9 of their papers we have counts for
8 papers · 1 filter
Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation
Changsun Lee, Sangjoon Park, Cheong-Il Shin +4
Recent medical vision-language models (VLMs) have shown promise in 2D medical image interpretation. However extending them to 3D medical imaging has been challenging due to computa…
LLM-driven Multimodal Target Volume Contouring in Radiation Oncology
Yujin Oh, Sangjoon Park, Hwa Kyung Byun +4
Target volume contouring for radiation therapy is considered significantly more challenging than the normal organ segmentation tasks as it necessitates the utilization of both imag…
Self-supervised Multi-modal Training from Uncurated Image and Reports Enables Zero-shot Oversight Artificial Intelligence in Radiology
Sangjoon Park, Eun Sun Lee, Kyung Sook Shin +2
Oversight AI is an emerging concept in radiology where the AI forms a symbiosis with radiologists by continuously supporting radiologists in their decision-making. Recent advances…
Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training
Sangjoon Park, Gwanghyun Kim, Jeongsol Kim +2
Federated learning, which shares the weights of the neural network across clients, is gaining attention in the healthcare sector as it enables training on a large corpus of decentr…
Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification
Sangjoon Park, Gwanghyun Kim, Yujin Oh +6
Developing a robust algorithm to diagnose and quantify the severity of COVID-19 using Chest X-ray (CXR) requires a large number of well-curated COVID-19 datasets, which is difficul…
Severity Quantification and Lesion Localization of COVID-19 on CXR using Vision Transformer
Gwanghyun Kim, Sangjoon Park, Yujin Oh +6
Under the global pandemic of COVID-19, building an automated framework that quantifies the severity of COVID-19 and localizes the relevant lesion on chest X-ray images has become i…
Vision Transformer for COVID-19 CXR Diagnosis using Chest X-ray Feature Corpus
Sangjoon Park, Gwanghyun Kim, Yujin Oh +6
Under the global COVID-19 crisis, developing robust diagnosis algorithm for COVID-19 using CXR is hampered by the lack of the well-curated COVID-19 data set, although CXR data with…
Deep Learning COVID-19 Features on CXR using Limited Training Data Sets
Yujin Oh, Sangjoon Park, Jong Chul Ye
Under the global pandemic of COVID-19, the use of artificial intelligence to analyze chest X-ray (CXR) image for COVID-19 diagnosis and patient triage is becoming important. Unfort…