Jeffrey Fessler

KLA sponsored prizes for three outstanding projects focused on improving image processing for neurosurgery and satellite applications and MRI reconstruction techniques.

Transparent optical sensor arrays combine with a specialized neural network in new University of Michigan prototype

Crockett’s dissertation will integrate two fields: image processing & machine learning and engineering education research

From adapting to remote office hours to completely redesigning exam content and format, we explore how one class, EECS 551 Matrix Methods for Signal Processing, Data Analysis, & Machine Learning, has had to reinvent itself for the times.

The interdisciplinary team was able to dramatically speed up the process while potentially doubling the quality of the image

The researchers’ imaging technique is fast, accurate, and reproducible

ECE postdoc Melissa Haskell works on improving functional magnetic resonance imaging so we can better measure and understand brain activity.

Researchers demonstrated the use of stacked, transparent graphene photodetectors combined with image processing algorithms to produce 3D images and range detection.

Electrical and Computer Engineering (ECE) faculty and students at Michigan are part of the revolution in data science that is happening today.

Students in EECS 556: Image Processing, explore methods to improve image processing in applications such as biomedical imaging and video and image compression

Award for outstanding doctoral candidates near the end of their study.

The course covers the theory and application of digital image processing, with applications in biomedical images, time-varying imagery, robotics, and optics.

Prof. Fessler has revolutionized the theory and practice of medical imaging with his group’s groundbreaking mathematical models and algorithms.

Prof. Fessler was surprised (and happy) to learn of this unique honor at the end of his final class for the semester.

In addition to being a professor of Electrical Engineering and Computer Science, Fessler is a professor of Biomedical Engineering and Radiology.

While 3D films are currently made using multiple cameras to reconstruct each frame, this new type of camera could record in 3D on its own.

Prof. Fessler has revolutionized medical imaging with groundbreaking mathematical models and algorithms that improve both safety and quality.

Ultra-low dose CT scans that provide superior image quality could not only benefit patients, but they could open up entirely new clinical applications.

In recognition of how the Electrical Engineering discipline has evolved, the two graduate programs, Electrical Engineering and Electrical Engineering: Systems, have merged to form one graduate program: Electrical and Computer Engineering.

The project entails investigating a recent paper and both reproducing and extending the research.

Hao’s research is focused on improving the quality of images from magnetic resonance imaging pulse design.

Mai has served as Community Service Co-chair of the Graduate Society of Women Engineers since arriving at Michigan in 2011.

The research group is using statistical signal processing to create crisper images with only 20% of the data required by a traditional MRI scan.

Nataraj is using big data techniques to transform the field of medical imaging

Nataraj’s research aims to generate higher-quality and faster MRI images, resulting in improved diagnostics of neurological disorders and autoimmune diseases.

Several of the cubes enabled research to progress to the point that faculty are applying for larger grants to continue the work.

This award recognizes outstanding contributions to the field of medical imaging science.

The course covers the theory and application of digital image processing.

Congratulations to the following recipients of 2012-13 College of Engineering Awards!

Fessler’s students have praised the collegial and collaborative environment of his lab, his careful balancing of freedom and guidance, and his attention to each student.

“We’re excited to be adding Veo to the measures we already have in place to ensure that we get diagnostic images using the lowest amount of radiation possible.”

Congratulations to the winning students!

The Barbour Scholarship, established in 1914, recognizes women at the University of Michigan of the highest academic and professional caliber.

Long’s work describes a new algorithm for performing model-based methods in a way that requires less computation yet provides improved image quality.