Motivation

1. Imaging technology is becoming increasingly significant in many scientific applications such as astronomy, medical imaging, military, video surveillance, iris scanning and microscopy (just to name a few!). My primary research interest is the development of numerical methods and software for problems arising in biomedical imaging applications.
   

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3. Every day doctors use imaging devices to diagnose diseases and prescribe appropriate treatments, but the collected raw data must be processed before it can be clinically useful. A major goal in image reconstruction is to develop efficient and robust numerical algorithms to compute clearer, more detailed images.
   

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5. For example, images are often degraded by blur. Image de-blurring is one example in which sophisticated computational techniques can be used to remove blur and noise from degraded images. However, a variety of computational difficulties may arise during the process, interfering with the accuracy of our restorations. We work on developing efficient approximation techniques that address these issues, and we hope that these algorithms can benefit many scientific applications.

Software

1. HyBR: An efficient implementation of a Lanczos based hybrid method for solving ill-posed inverse problems.

Primary Research

Some Links

Some friends and colleagues: