Seoul, South Korea

Eung June Shim

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Imagoworks Inc.. Active years: 2026.

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Eung June Shim: Innovator in Maxillofacial Imaging Technology

Introduction

Eung June Shim is a prominent inventor based in Seoul, South Korea. He has made significant contributions to the field of medical imaging, particularly in the area of maxillofacial bone segmentation using advanced deep learning techniques. His innovative approach has the potential to enhance the accuracy and efficiency of medical diagnoses.

Latest Patents

Eung June Shim holds a patent for a method titled "Method of automatic segmentation of maxillofacial bone in CT image using deep learning." This method involves receiving input CT slices that include the maxillofacial bone and segmenting these slices into a mandible and a portion of the maxillofacial bone excluding the mandible. The process utilizes a convolutional neural network structure to accumulate 2D segmentation results, ultimately reconstructing a 3D segmentation result. The convolutional neural network structure features an encoder with distinct operations in the same layer and a decoder that similarly incorporates different operations.

Career Highlights

Eung June Shim is associated with Imagoworks Inc., where he applies his expertise in deep learning and medical imaging. His work is instrumental in advancing the capabilities of imaging technologies, particularly in the healthcare sector.

Collaborations

Eung June Shim collaborates with talented individuals such as Seungbin Park and Youngjun Kim. Their combined efforts contribute to the innovative projects at Imagoworks Inc., fostering a collaborative environment that drives technological advancements.

Conclusion

Eung June Shim's contributions to the field of medical imaging through his patented methods exemplify the impact of innovation in healthcare. His work not only enhances diagnostic processes but also showcases the potential of deep learning in medical applications.

Profile summary based on public USPTO records.
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