Charlottesville, VA, United States of America

Mohammad Abdishektaei

USPTO Granted Patents = 1 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2022

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1 patent (USPTO):Explore Patents

Title: Innovations in MRI Technology by Mohammad Abdishektaei

Introduction

Mohammad Abdishektaei is an accomplished inventor based in Charlottesville, VA. He has made significant contributions to the field of medical imaging, particularly in the area of MRI technology. His innovative approach focuses on enhancing image quality while reducing scan times, which is crucial for patient care.

Latest Patents

Abdishektaei holds a patent for a "Method and system for deep convolutional neural net for artifact suppression in dense MRI." This patent addresses the challenge of suppressing artifacts in MRI image acquisition data. The method utilizes a Convolutional Neural Network (CNN) to suppress artifact-generating echoes, providing a more accurate representation of the scanned area. The U-NET CNN is trained using phase-cycled artifact-free images, allowing for effective comparison with received displacement encoded stimulated echo (DENSE) images. This innovative system generates artifact-free images, eliminating the need for additional data acquisition and significantly shortening scan times in DENSE MRI.

Career Highlights

Abdishektaei is affiliated with the University of Virginia, where he continues to advance research in medical imaging technologies. His work has garnered attention for its potential to improve diagnostic accuracy and efficiency in MRI procedures.

Collaborations

He collaborates with notable colleagues, including Xue Feng and Xiaoying Cai, who contribute to the research and development of advanced imaging techniques.

Conclusion

Mohammad Abdishektaei's contributions to MRI technology exemplify the impact of innovative thinking in medical imaging. His patent for artifact suppression using deep learning techniques represents a significant advancement in the field, promising to enhance patient outcomes through improved imaging quality and efficiency.

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