Thin-Slice Brain CT Image Quality and Lesion Detection Evaluation in Deep Learning Reconstruction Algorithm.

Journal: Clinical neuroradiology
Published Date: Jul 23, 2025

Abstract

BACKGROUND: Clinical evaluation of Artificial Intelligence (AI)-based Precise Image (PI) algorithm in brain imaging remains limited. PI is a deep-learning reconstruction (DLR) technique that reduces image noise while maintaining a familiar Filtered Back Projection (FBP)-like appearance at low doses. This study aims to compare PI, Iterative Reconstruction (IR), and FBP-in improving image quality and enhancing lesion detection in 1.0 mm thin-slice brain computed tomography (CT) images.

Authors

  • Jiali Sun
    College of Science, Nanjing Agricultural University, Nanjing, 210095, China.
  • Hui Yao
    Philips CT Clinical Science Global, Philips Health Technology Co. Ltd, 258 Zhong Yuan Road, Suzhou Industrial Park, Suzhou, China.
  • Tailin Han
    Philips CT Clinical Support, Great China, Philips Healthcare, Floor 7, Building 2, World Profit Center, No. 16 Tianze Road, Beijing, Chaoyang District, China.
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Le Yang
    Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo, NY 14214, USA.
  • Xizhe Hao
    Philips CT Clinical Science Global, Philips Health Technology Co. Ltd, 258 Zhong Yuan Road, Suzhou Industrial Park, Suzhou, China.
  • Su Wu

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