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ECE Colloquium Series – Prof. Il Yong Chun on image processing

March 4 @ 4:00 pm - 5:00 pm

As part of the Eleanore Hale Wilson Lecture Series*, ECE is proud to present:

Professor Il Yong Chun

University of Hawai’i, Manoa

Zoom Link: https://umn.zoom.us/j/92842770045

Abstract:

“Extreme” imaging collects extremely undersampled or inaccurate measurements, and provides significant benefits to diverse imaging applications. The examples in medical imaging include highly undersampled MRI to reduce imaging time, ultra‐low‐dose CT to reduce radiation dose and cancer risk from CT scanning, etc. However, obtaining an accurate image within a reasonable computing time is challenging in extreme imaging. Since 2016, researchers have been applying a deep regression convolutional neural network (CNN) to conquer extreme imaging problems. However, existing non‐iterative regression CNNs have overfitting risks. This talk introduces my group’s contributions in regulating the overfitting risks via iterative neural network (INN) architectures using model‐based image reconstruction (MBIR) perspectives. The first half of this talk introduces learning and optimization theories for unsupervised training of CNNs, convolutional analysis operator learning (CAOL). The second half of this talk introduces the current state‐of‐the‐art INN architecture, Momentum‐Net, that achieves the fastest and most accurate MBIR within a finite time, and can solve a wide range of inverse imaging problems. The talk will show benefits of CAOL and Momentum‐Net in diverse extreme imaging applications, such as low‐dose CT, light‐field imaging with limited focal stack data, low‐count PET, and material decomposition in dual‐energy CT. Making extreme imaging practically feasible breaks new ground in providing safe and comfortable medical imaging to patients, and high‐resolution photography that is potentially useful in autonomous driving and augmented reality.

Host: Professor Mehmet Akçakaya

*Established in 2009, the Eleanore Hale Wilson Fund supports engineering field leaders for travel to Minnesota to share their expertise and discoveries with University of Minnesota graduate students, faculty, and alumni. The fund also supports the receptions held in honor of each speaker.

Details

Date:
March 4
Time:
4:00 pm - 5:00 pm
Website:
https://umn.zoom.us/j/92842770045