Artificial intelligence iterative imaging reconstruction with low-dose CT scans for hepatic metastases
Xiang Liu, Zhi-Lei Zhang, Xiao-Hui Qi, Jiang-Yang Pan, Xue-Li Fan, Jing Liu, Yi-Ting Sun, Qi Wang · 2026
Read Artificial intelligence iterative imaging reconstruction with low-dose CT scans for hepatic metastases by Xiang Liu, Zhi-Lei Zhang, Xiao-Hui Qi, Jiang-Yang Pan, Xue-Li Fan, Jing Liu, Yi-Ting Sun, Qi Wang (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13369155.txt.
Description
Xiang Liu and co-authors test low dose CT with artificial intelligence rebuilding for liver metastases in a 2026 study. Contrast CT is a standard way to check liver spread of cancer. Lower dose scans cut radiation but add noise. Thirty-two patients get both a standard dose scan and a reduced dose scan in the same session.
The reduced dose cuts radiation by about eighty percent, they report. Plain rebuilding of the low dose images finds far fewer nodules. An artificial intelligence iterative method at a mid setting finds over ninety-three percent of the nodules seen at full dose. Very small nodules remain the hardest to catch.
Catalog record
| CREATOR | Xiang Liu, Zhi-Lei Zhang, Xiao-Hui Qi, Jiang-Yang Pan, Xue-Li Fan, Jing Liu, Yi-Ting Sun, Qi Wang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 42 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |