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Total 12건 1 페이지

2024-09-09

Automated Idiopathic Normal-Pressure Hydrocephalus Diagnosis via Artificial Intelligence-Based 3D T1 MRI Volumetric Analysis

Joonhyung Lee, Dana Kim, Chong Hyun Suh, Suyoung Yun, Kyu Sung Choi, Seungjun Lee, Wooseok Jung, Jinyoung Kim, Hwon Heo, Woo Hyun Shim, Sungyang Jo, Sun Ju Chung, Jae-Sung Lim, Ho Sung Kim, Sang Joon Kim and Jae-Hong Lee
2024-06-21

Impact of white matter hyperintensity volumes estimated by automated methods using deep learning on stroke outcomes in small vessel occlusion stroke

Minwoo Lee, Chong Hyun Suh, Jong-Hee Sohn, Chulho Kim, Sang-Won Han, Joo Hye Sung, Kyung-Ho Yu, Jae-Sung Lim, Sang-Hwa Lee
2024-02-22

Deep learning-based, fully automated, pediatric brain segmentation

Min-Jee Kim, EunPyeong Hong, Mi-Sun Yum, Yun-Jeong Lee, Jinyoung Kim & Tae-Sung Ko
2023-09-22

Comparison of Normative Percentiles of Brain Volume Obtained from NeuroQuant® vs. DeepBrain® in the Korean Population: Correlation with Cranial Shape

Mi Hyun Yang, Eun Hee Kim, Eun Sun Choi, Hongseok Ko
2023-09-01

Development and validation of a deep learning-based automatic segmentation model for assessing intracranial volume: comparison with NeuroQuant, FreeSurfer, and SynthSeg

Pae Sun Suh, Wooseok Jung, Chong Hyun Suh, Jinyoung Kim, Jio Oh, Hwon Heo, Woo Hyun Shim, Jae-Sung Lim, Jae-Hong Lee, Ho Sung Kim, Sang Joon Kim
2023-05-12

Development and validation of an automatic classification algorithm for the diagnosis of Alzheimer’s disease using a high-performance interpretable deep learning network

Ho Young Park, Woo Hyun Shim, Chong Hyun Suh, Hwon Heo, Hyun Woo Oh, Jinyoung Kim, Jinkyeong Sung, Jae-Sung Lim, Jae-Hong Lee, Ho Sung Kim & Sang Joon Kim
2023-03-15

Risk estimation for idiopathic normal-pressure hydrocephalus: development and validation of a brain morphometry–based nomogram

Su Young Yun, Kyu Sung Choi, Chong Hyun Suh, Soo Chin Kim, Hwon Heo, Woo Hyun Shim, Sungyang Jo, Sun Ju Chung, Jae-Sung Lim, Jae-Hong Lee, Donghyun Kim, Seon-Ok Kim, Wooseok Jung, Ho Sung Kim, Sang Joon Kim & Ji-Hoon Kim
2022-10-06

Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation

Wooseok Jung, Chong Hyun Suh, Woo Hyun Shim, Jinyoung Kim, Dongsoo Lee, Changhyun Park, Seo Taek Kong, Kyu-Hwan Jung, Hwon Heo & Sang Joon Kim
2022-10-06

Augmenting Magnetic Resonance Imaging with Tabular Features for Enhanced and Interpretable Medial Temporal Lobe Atrophy Prediction

Dongsoo Lee, Chong Hyun Suh, Jinyoung Kim, Wooseok Jung, Changhyun Park, Kyu-Hwan Jung, Seo Taek Kong, Woo Hyun Shim, Hwon Heo & Sang Joon Kim
2022-09-15

Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia

Leehi Joo ,Woo Hyun Shim ,Chong Hyun Suh ,Su Jin Lim,Hwon Heo,Woo Seok Kim,Eunpyeong Hong,Dongsoo Lee,Jinkyeong Sung,Jae-Sung Lim,Jae-Hong Lee,Sang Joon Kim
2022-09-13

Agreement and Reliability between Clinically Available Software Programs in Measuring Volumes and Normative Percentiles of Segmented Brain Regions

Huijin Song, Seun Ah Lee, Sang Won Jo, Suk-Ki Chang, Yunji Lim, Yeong Seo Yoo, Jae Ho Kim, Seung Hong Choi, and Chul-Ho Sohn
2020-03-04

Development and Validation of a Deep Learning–Based utomatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images

C.H. Suh, W.H. Shim, S.J. Kim, J.H. Roh, J.-H. Lee, M.-J. Kim, S. Park, W. Jung, J. Sung, G.-H. Jahng, and for the Alzheimer’s Disease Neuroimaging Initiative

* VUNO Med®-DeepCARS® has not yet received FDA clearance for commercial use.

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Publications

Automated Idiopathic Normal-Pressure Hydrocephalus Diagnosis via Artificial Intelligence-Based 3D T1 MRI Volumetric Analysis

Impact of white matter hyperintensity volumes estimated by automated methods using deep learning on stroke outcomes in small vessel occlusion stroke

Deep learning-based, fully automated, pediatric brain segmentation

Comparison of Normative Percentiles of Brain Volume Obtained from NeuroQuant® vs. DeepBrain® in the Korean Population: Correlation with Cranial Shape

Development and validation of a deep learning-based automatic segmentation model for assessing intracranial volume: comparison with NeuroQuant, FreeSurfer, and SynthSeg

Development and validation of an automatic classification algorithm for the diagnosis of Alzheimer’s disease using a high-performance interpretable deep learning network

Risk estimation for idiopathic normal-pressure hydrocephalus: development and validation of a brain morphometry–based nomogram

Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation

Augmenting Magnetic Resonance Imaging with Tabular Features for Enhanced and Interpretable Medial Temporal Lobe Atrophy Prediction

Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia

Agreement and Reliability between Clinically Available Software Programs in Measuring Volumes and Normative Percentiles of Segmented Brain Regions

Development and Validation of a Deep Learning–Based utomatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images