Jae-Hun Kim

Assistant Professor

Samsung Medical Center

South Korea

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Dr. Jae-Hun Kim is an Assistant Professor at Samsung Medical Center in South Korea. His research focuses on advanced imaging techniques and artificial intelligence applications in medical diagnostics, particularly related to liver donor assessments and cancer therapies. Recent publications include studies on deep learning for MRI interpretation and 3D auto-segmentation in preoperative planning. Dr. Kim is dedicated to enhancing diagnostic accuracy and treatment outcomes through innovative imaging methodologies.

Articles (19)

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2024

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Won-Jin Moon

Professor

Konkuk University Medical Center

SOUTH KOREA

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Bang-bon Koo

Assistant Professor

Boston University School of Medicine

UNITED STATES

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Jae-Won Joh

Professor

Sungkyunkwan University School of Medicine

SOUTH KOREA

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Eun Sook Ko

SOUTH KOREA

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Jae-Won Jang

Associate profressor

Seoul National University Hospital

SOUTH KOREA

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Woo Kyoung Jeong

Associate Professor

Samsung Medical Center

SOUTH KOREA

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Jae-Hun Kim

Research Interests

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About

Articles (19)

3D auto-segmentation of biliary structure of living liver donors using magnetic resonance cholangiopancreatography for enhanced preoperative planning

Comprehensive deep learning-based assessment of living liver donor CT angiography: from vascular segmentation to volumetric analysis

Deep Cascade of Convolutional Neural Networks for Quantification of Enlarged Perivascular Spaces in the Basal Ganglia in Magnetic Resonance Imaging

Efficient data labeling strategies for automated muscle segmentation in lower leg MRIs of Charcot-Marie-Tooth disease patients

Prognostic Role of Pre-Treatment Body Composition Parameters in Patients Undergoing First-Line Immunotherapy for Metastatic Renal Cell Carcinoma

nnU-Net-Based Pancreas Segmentation and Volume Measurement on CT Imaging in Patients with Pancreatic Cancer

Diagnostic Tools for Alzheimer’s Disease: A Narrative Review Based on Our Own Research Experience

Fat Loss in Patients with Metastatic Clear Cell Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors

Automated 3D liver segmentation from hepatobiliary phase MRI for enhanced preoperative planning

Predicting Non-Small-Cell Lung Cancer Survival after Curative Surgery via Deep Learning of Diffusion MRI

Impact of Skeletal Muscle Loss and Visceral Obesity Measured Using Serial CT on the Prognosis of Operable Breast Cancers in Asian Patients

Serial Observations of Muscle and Fat Mass as Prognostic Factors for Deceased Donor Liver Transplantation

Defining the optimal target for anterior thalamic deep brain stimulation in patients with drug-refractory epilepsy

Dynamic contrast-enhanced mri for response evaluation of non-small cell lung cancer in therapy with epidermal growth factor receptor tyrosine kinase inhibitors: A pilot study

Prognostic significance of sarcopenia in microsatellite-stable gastric cancer patients treated with programmed death-1 inhibitors

Neuroimaging Markers for Studying Gulf-War Illness: Single-Subject Level Analytical Method Based on Machine Learning

Texture analysis using T1-weighted images for muscles in Charcot-Marie-Tooth disease patients and volunteers

The effects of sarcopenia and sarcopenic obesity after pancreaticoduodenectomy in patients with pancreatic head cancer

The role of histogram analysis of grayscale sonograms to differentiate thyroid nodules identified by 18F-FDG PET-CT

Collaborators (11)

Hyun Su Kim

Yeonsil Moon

ChoonHyuck David Kwon

Sang-Yong Eom

Ji Hyun Lee

Won-Jin Moon

Bang-bon Koo

Jae-Won Joh

Eun Sook Ko

Jae-Won Jang

Woo Kyoung Jeong

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