Abdullah Hussein Owaidh

Title: Innovations in Breast Density Classification by Abdullah Hussein Owaidh

Introduction

Abdullah Hussein Owaidh is an accomplished inventor based in Dhahran, Saudi Arabia. He has made significant contributions to the field of medical imaging, particularly in the classification of breast density from mammographic imagery. His innovative approach utilizes advanced computational techniques to enhance diagnostic accuracy.

Latest Patents

Owaidh holds a patent for a "Method, system and computer program product for breast density classification using parts-based local features." This invention involves an automated content-based image retrieval method that classifies breast density from mammographic images. The process begins with the pre-processing of raw digital mammogram images to remove noise and enhance contrast. Following this, pectoral muscle segmentation is performed to produce region of interest (ROI) images. These ROI images are then decomposed using non-negative matrix factorization (NMF), which imposes a non-negative sparsity constraint and reconstruction quality measures on the extracted factors. The retained NMF factors are utilized by kernel matrix-based support vector machines to classify the mammogram images into breast density categories. The NMF-based method has been shown to achieve higher classification accuracy compared to traditional principal component analysis (PCA) methods.

Career Highlights

Owaidh is affiliated with King Fahd University of Petroleum and Minerals, where he contributes to research and development in the field of medical imaging. His work has garnered attention for its innovative approach and practical applications in healthcare.

Collaborations

Owaidh collaborates with Lahouari Ghouti, enhancing the research output and innovation in their projects. Their partnership exemplifies the importance of teamwork in advancing technological solutions in medical imaging.

Conclusion

Abdullah Hussein Owaidh's contributions to breast density classification through innovative methodologies highlight the intersection of technology and healthcare. His work not only improves diagnostic processes but also sets a precedent for future innovations in medical imaging.