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A Rare Case of Cardiac Neurofibroma in a Patient with Neurofibromatosis Type 1: Radiologic Findings
Seo Sanghyun,Rho Ji Young 대한영상의학회 2021 대한영상의학회지 Vol.82 No.5
Neurofibromatosis type 1 (NF1) is a relatively common inherited disorder characterized by the formation of neurofibromas, pigmentary abnormalities of the skin, Lisch nodules of the iris, and skeletal abnormalities. Multiple cutaneous neurofibromas are benign nerve sheath tumors and the main manifestation of NF1. Cardiac neurofibroma associated with NF1 is very rare, and few cases have been reported in the literature. Herein, we present the CT and MRI findings of a surgically confirmed left ventricular neurofibroma in a 32-year-old female with NF1.
Transfer Learning based Parameterized 3D Mesh Deformation with 2D Stylized Cartoon Character
Sanghyun Byun,Bumsoo Kim,신원섭,Yonghoon Jung,Sanghyun Seo 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.11
As interest in the metaverse has grown, there has been a demand for avatars that can represent individual users. Consequently, research has been conducted to reduce the time and cost required for the current 3D human modeling process. However, the recent automatic generation of 3D humans has been focused on creating avatars with a realistic human form. Furthermore, the existing methods have limitations in generating avatars with imbalanced or unrealistic body shapes, and their utilization is limited due to the absence of datasets. Therefore, this paper proposes a new framework for automatically transforming and creating stylized 3D avatars. Our research presents a definitional approach and methodology for creating non-realistic character avatars, in contrast to previous studies that focused on creating realistic humans. We define a new shape representation parameter and use a deep learning–based method to extract character body information and perform automatic template mesh transformation, thereby obtaining non-realistic or unbalanced human meshes. We present the resulting outputs visually, conducting user evaluations to demonstrate the effectiveness of our proposed method. Our approach provides an automatic mesh transformation method tailored to the growing demand for avatars of various body types and extends the existing method to the 3D cartoon stylized avatar domain.