Khaled Salem Younis

Title: Innovations of Khaled Salem Younis

Introduction

Khaled Salem Younis is an accomplished inventor based in Parma Heights, OH (US). He has made significant contributions to the field of deep learning and medical imaging, holding a total of five patents. His work focuses on optimizing model performance and enhancing image analysis techniques.

Latest Patents

One of his latest patents is titled "Image Harmonization for Deep Learning Model Optimization." This patent describes techniques for optimizing deep learning model performance by using image harmonization as a pre-processing step. The method involves decomposing an input image into sub-images and harmonizing these sub-images with corresponding reference sub-images based on various statistical values. This results in modified sub-images that can be combined into a harmonized image, improving the model's performance.

Another notable patent is "Systems and Methods for Detecting Laterality of a Medical Image." This invention provides a system for detecting the laterality of x-ray images using a neural network model. The model analyzes unclassified x-ray images and assigns a laterality class. If the assigned class does not match the target laterality, the system adjusts the image to derive a corrected version, ensuring accurate medical analysis.

Career Highlights

Khaled Salem Younis is currently employed at GE Precision Healthcare LLC, where he continues to innovate in the healthcare technology sector. His work has a profound impact on improving diagnostic processes and enhancing the capabilities of deep learning models in medical imaging.

Collaborations

Khaled collaborates with talented professionals such as Gireesha Chinthamani Rao and Gopal Biligeri Avinash. Their combined expertise contributes to the advancement of innovative solutions in healthcare technology.

Conclusion

Khaled Salem Younis is a prominent inventor whose work in deep learning and medical imaging is paving the way for advancements in healthcare technology. His patents reflect a commitment to improving model performance and diagnostic accuracy.