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Labeling Lateral Prefrontal Sulci using Spherical Data Augmentation and Context-aware Training

Apr. 1, 2021—Ilwoo Lyu, Shunxing Bao, Lingyan Hao, Jewelia Yao, Jacob Miller, Willa Voorhies, Warren Taylor, Silvia Bunge, Kevin Weiner, Bennett Landman. “Labeling Lateral Prefrontal Sulci using Spherical Data Augmentation and Context-aware Training”. NeuroImage, 229, 117758, 2021. [Full text][Code] Abstract The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal regions, whereas shallow...

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Validation of group-wise registration for surface-based functional MRI analysis

Oct. 20, 2020—Chang Yu, Yue Liu, Leon Cai, Cailey Kerley, Kaiwen Xu, Katherine Aboud, Warren Taylor, Hakmook Kang, Andrea Shafer, Lori Beason-Held, Susan Resnick, Bennett Landman, Ilwoo Lyu. “Validation of group-wise registration for surface-based functional MRI analysis”. SPIE Medical Imaging 2021. [Full text][Code] Abstract Resting-state functional MRI (rsfMRI) provides important information for studying and mapping the activities...

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Automatic Labeling of Cortical Sulci using Convolutional Neural Networks in a Developmental Cohort

Apr. 20, 2020—Lingyan Hao, Shunxing Bao, Yucheng Tang, Riqiang Gao, Prasanna Parvathaneni, Jacob Miller, Willa Voorhies, Jewelia Yao, Silvia Bunge, Kevin Weiner, Bennett Landman, Ilwoo Lyu. “Automatic Labeling of Cortical Sulci using Convolutional Neural Networks in a Developmental Cohort”. IEEE International Symposium on Biomedical Imaging (ISBI) 2020, IEEE, 412-415, Iowa City, Iowa, USA, 2020. [Full text][Code] Abstract...

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Improving Human Cortical Sulcal Curve Labeling in Large Scale Cross-Sectional MRI using Deep Neural Networks

Nov. 11, 2019—Prasanna Parvathaneni, Vishwesh Nath, Maureen McHugo, Yuankai Huo, Susan Resnick, Neil Woodward, Bennett Landman,¬†Ilwoo Lyu. “Improving Human Cortical Sulcal Curve Labeling in Large Scale Cross-Sectional MRI using Deep Neural Networks”. Journal of Neuroscience Methods, 324, 108311, 2019. [Full text] Abstract BACKGROUND: Human cortical primary sulci are relatively stable landmarks and commonly observed across the population....

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Hierarchical Spherical Deformation for Cortical Surface Registration

Nov. 11, 2019—Ilwoo Lyu, Hakmook Kang, Neil D. Woodward, Martin A. Styner and Bennett A. Landman. “Hierarchical Spherical Deformation for Cortical Surface Registration”. Medical Image Analysis, 57, pp. 72-88, 2019. [Full text][Code][Docker] Abstract We present hierarchical spherical deformation for a group-wise shape correspondence to address template selection bias and to minimize registration distortion. In this work, we...

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Hierarchical Spherical Deformation for Shape Correspondence

Oct. 26, 2018—Ilwoo Lyu, Martin A. Styner and Bennett A. Landman. “Hierarchical Spherical Deformation for Shape Correspondence”. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain, 2018. [Full text][Code][Docker] Abstract We present novel spherical deformation for a landmark-free shape correspondence in a group-wise manner. In this work, we aim at both addressing...

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TRACE: A Topological Graph Representation for Automatic Sulcal Curve Extraction

Dec. 28, 2017—Ilwoo Lyu, Sun Hyung Kim, Neil D. Woodward, Martin A. Styner and Bennett A. Landman. “TRACE: A Topological Graph Representation for Automatic Sulcal Curve Extraction “. IEEE Transactions on Medical Imaging 37(7), pp. 1653-1663, 2018. [Full text][Code][Docker] Abstract A proper geometric representation of the cortical regions is a fundamental task for cortical shape analysis and...

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Sulcal Depth-based Cortical Shape Analysis in Normal Healthy Control and Schizophrenia Groups

Dec. 11, 2017—Ilwoo Lyu, Hakmook Kang, Neil D. Woodward, and Bennett A. Landman. “Sulcal Depth-based Cortical Shape Analysis in Normal Healthy Control and Schizophrenia Groups”. SPIE Medical Imaging 2018. Abstract Sulcal depth is an important marker of brain anatomy in neuroscience/neurological function. Previously, sulcal depth has been explored at the region-of-interest (ROI) level to increase statistical sensitivity...

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