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Yong Long receives Best Poster Award for work in medical imaging

Long's work describes a new algorithm for performing model-based methods in a way that requires less computation yet provides improved image quality.| Short Read
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Yong Long, doctoral student in Electrical Engineering:Systems, and co-authors Prof. Jeffrey A. Fessler(Professor of EECS, Biomedical Engineering, and Radiology) and Prof. James M. Balter (Professor of Radiation Oncology) received a Best Poster award at the 10th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, held in Beijing, China. Their paper was titled, “A 3D Forward and Back-Projection Method for X-Ray CT Using Separable Footprint.”

Model-based methods for 3D tomographic image reconstruction have the potential to significantly improve image quality and reduce patient X-ray dose in medical computed tomography (CT) scans. The primary drawback of model-based methods compared to conventional image reconstruction methods is the increased computation time. This work describes a new algorithm for performing the most computationally expensive portion of model-based methods in a way that requires less computation than traditional methods yet provides improved image quality. The method is being evaluated by U-M researchers on patient X-ray CT scans for possible use in next generation CT systems. It is also being investigated for applications in radiation therapy.

Long and Fessler
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The electrons absorb laser light and set up “momentum combs” (the hills) spanning the energy valleys within the material (the red line). When the electrons have an energy allowed by the quantum mechanical structure of the material—and also touch the edge of the valley—they emit light. This is why some teeth of the combs are bright and some are dark. By measuring the emitted light and precisely locating its source, the research mapped out the energy valleys in a 2D crystal of tungsten diselenide. Credit: Markus Borsch, Quantum Science Theory Lab, University of Michigan.

Mapping quantum structures with light to unlock their capabilities

Rather than installing new “2D” semiconductors in devices to see what they can do, this new method puts them through their paces with lasers and light detectors. | Medium Read