A Perspective on Deep Imaging

09/10/2016
by   Ge Wang, et al.
0

The combination of tomographic imaging and deep learning, or machine learning in general, promises to empower not only image analysis but also image reconstruction. The latter aspect is considered in this perspective article with an emphasis on medical imaging to develop a new generation of image reconstruction theories and techniques. This direction might lead to intelligent utilization of domain knowledge from big data, innovative approaches for image reconstruction, and superior performance in clinical and preclinical applications. To realize the full impact of machine learning on medical imaging, major challenges must be addressed.

READ FULL TEXT

page 4

page 5

research
08/10/2020

Deep learning for photoacoustic imaging: a survey

Machine learning has been developed dramatically and witnessed a lot of ...
research
06/23/2019

A Review on Deep Learning in Medical Image Reconstruction

Medical imaging is crucial in modern clinics to guide the diagnosis and ...
research
03/21/2019

Reconstruction Methods in THz Single-pixel Imaging

The aim of this paper is to discuss some advanced aspects of image recon...
research
01/27/2014

Computing support for advanced medical data analysis and imaging

We discuss computing issues for data analysis and image reconstruction o...
research
12/17/2013

Performance Engineering for a Medical Imaging Application on the Intel Xeon Phi Accelerator

We examine the Xeon Phi, which is based on Intel's Many Integrated Cores...
research
06/11/2022

Learned reconstruction with convergence guarantees

In recent years, deep learning has achieved remarkable empirical success...
research
12/30/2014

Holistic random encoding for imaging through multimode fibers

The input numerical aperture (NA) of multimode fiber (MMF) can be effect...

Please sign up or login with your details

Forgot password? Click here to reset