Leonard Sunwoo

Professor

Seoul National University Hospital

South Korea

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Professor Leonard Sunwoo is a faculty member at Seoul National University Bundang Hospital in South Korea. His research focuses on the applications of artificial intelligence in neuroimaging, particularly in the context of acute and degenerative neurologic disorders, stroke detection, and lung cancer analysis. Recent publications highlight advancements in automated detection and classification in medical imaging, contributing to improved clinical outcomes.

Articles (18)

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2025

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2021

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2021

Collaborators (11)

Tackeun Kim

Associate Professor

Seoul National University Hospital

SOUTH KOREA

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Kyong Joon Lee

Assistant Professor

Seoul National University Hospital

SOUTH KOREA

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Cheolkyu Jung

Seoul National University Hospital

SOUTH KOREA

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You-Ri Kang

Assistant Professor

Chonnam National University Hospital

SOUTH KOREA

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Hunjong Lim

Clinical Assistant Professor (Specialty: Thyroid Radiology)

Seoul National University Hospital

SOUTH KOREA

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Yun Jung Bae

Seoul National University College of Medicine

SOUTH KOREA

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Byung Se Choi

Seoul National University Hospital

SOUTH KOREA

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Wi-Sun Ryu

Assistant Professor

Pusan National University Yangsan Hospital

SOUTH KOREA

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Eunju Cha

Sookmyung Women's University

SOUTH KOREA

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Beom Joon Kim

Assistant Professor

Seoul National University Hospital

SOUTH KOREA

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Jinhee Jang

The Catholic University of Korea

SOUTH KOREA

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Leonard Sunwoo

Research Interests

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Articles (18)

Artificial intelligence in neuroimaging with a focus on acute and degenerative neurologic disorders: a narrative review

Segmentation of the Hyperdense Artery Sign on Noncontrast CT in Ischemic Stroke Using Artificial Intelligence

Automated Prediction of Proximal Middle Cerebral Artery Occlusions in Noncontrast Brain Computed Tomography

Automated detection of large vessel occlusion using deep learning: a pivotal multicenter study and reader performance study

Automated Detection of Steno-Occlusive Lesion on Time-of-Flight MR Angiography: An Observer Performance Study

Integrating Clinical Data and Medical Imaging in Lung Cancer: Feasibility Study Using the Observational Medical Outcomes Partnership Common Data Model Extension

Automated Pathologic TN Classification Prediction and Rationale Generation From Lung Cancer Surgical Pathology Reports Using a Large Language Model Fine-Tuned With Chain-of-Thought: Algorithm Development and Validation Study

Intracranial steno-occlusive lesion detection on time-of-flight MR angiography using multi-task learning

A Nationwide Web-Based Survey of Neuroradiologists’ Perceptions of Artificial Intelligence Software for Neuro-Applications in Korea

Risk Prediction of Emergency Department Visits in Patients With Lung Cancer Using Machine Learning: Retrospective Observational Study

Predictive accuracy of T2-FLAIR mismatch sign for the IDH-mutant, 1p/19q noncodeleted low-grade glioma: An updated systematic review and meta-analysis

Impact of Diffusion–Perfusion Mismatch on Predicting Final Infarction Lesion Using Deep Learning

Spider U-Net: Incorporating Inter-Slice Connectivity Using LSTM for 3D Blood Vessel Segmentation

Deep Learning for Diagnosis of Paranasal Sinusitis Using Multi-View Radiographs

Two-stage deep learning for accelerated 3D time-of-flight MRA without matched training data

Comprehensive assessments of the open mouth dynamic maneuver and metal artifact reduction algorithm on computed tomography images of the oral cavity and oropharynx

Robustness of Deep Learning Algorithm to Varying Imaging Conditions in Detecting Low Contrast Objects in Computed Tomography Phantom Images: In Comparison to 12 Radiologists

Brain metastasis detection using machine learning: a systematic review and meta-analysis

Collaborators (11)

Tackeun Kim

Kyong Joon Lee

Cheolkyu Jung

You-Ri Kang

Hunjong Lim

Yun Jung Bae

Byung Se Choi

Wi-Sun Ryu

Eunju Cha

Beom Joon Kim

Jinhee Jang

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