Deep learning CT reconstruction improves liver metastases detection.

ABSTRACT:

Objectives

Detection of liver metastases is crucial for guiding oncological management. Computed tomography through iterative reconstructions is widely used in this indication but has certain limitations. Deep learning image reconstructions (DLIR) use deep neural networks to achieve a significant noise reduction compared to iterative reconstructions. While reports have demonstrated improvements in image quality, their impact on liver metastases detection remains unclear. Our main objective was to determine whether DLIR affects the number of detected liver metastasis. Our secondary objective was to compare metastases conspicuity between the two reconstruction methods.

Methods

CT images of 121 patients with liver metastases were reconstructed using a 50% adaptive statistical i

SUBMITTER: Kanan A 

PROVIDER: S-EPMC11227486 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature