Markov random field texture generation with an internalized database using a conditional encoder-decoder structure Conference Paper
| Authors: | Gao, Y.; Bai, T.; Lu, S.; Chang, S.; Zhang, H.; Hoshmand-Kochi, M.; Liang, Z. |
| Editors: | Zhao, W.; Yu, L. |
| Title: | Markov random field texture generation with an internalized database using a conditional encoder-decoder structure |
| Conference Title: | Medical Imaging 2022: Image Processing |
| Abstract: | The tissue specific MRF type texture prior (MRFt) proposed in our previous work has been demonstrated to be advantageous in various clinical tasks. However, this MRFt model requires a previous full-dose CT (FdCT) scan of the same patient to extract the texture information for LdCT reconstructions. This requirement may not be met in practice. To alleviate this limitation, we propose to build a MRFt generator by internalizing a database with paired FdCT and LdCT scans using a (conditional) encoder-decoder structure model. We denote this method as the MRFtG-ConED. This generation model depends only on physiological features thus is robust for ultra-low dose CT scans (i.e., dosage < 10mAs). When the dosage is not extremely low (i.e., dosage > 10mAs), some texture information from LdCT images reconstructed by filtered back projection (FBP) can be also used to provide extra information. © 2022 SPIE. |
| Keywords: | physiology; computerized tomography; medical imaging; tissue; textures; markov random fields; ldct; ct-scan; markov processes; physiological models; texture information; signal encoding; decoding; conditional encoder-decoder structure; physiological knowledge; tissue specific mrf prior; information filtering; decoder structures; encoder-decoder; tissue specifics |
| Journal Title | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
| Volume: | 12031 |
| Conference Dates: | 2022 Feb 20-23 |
| Conference Location: | San Diego, CA |
| ISBN: | 1605-7422 |
| Publisher: | SPIE |
| Date Published: | 2022-04-04 |
| Start Page: | 120311G |
| Language: | English |
| DOI: | 10.1117/12.2613033 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference Paper -- Export Date: 1 July 2022 -- Source: Scopus |
