Usefulness of four-dimensional noise reduction filtering using a similarity algorithm in low-dose dynamic computed tomography for the evaluation of breast cancer: a preliminary study
Daichi Uraoka, Megumi Matsuda, Yuki Tanabe, Naoto Kawaguchi, Chihiro Nishiyama, Ayaka Okada, Koichiro Uda, Hiroshi Suekuni, Hikaru Nishiyama, Yoshiaki Kamei, Mie Kurata, Riko Kitazawa, Shota Nakano, Teruhito Kido

TL;DR
A new noise reduction technique improves image quality and tumor visibility in low-dose CT scans for breast cancer evaluation.
Contribution
This study demonstrates that 4D-SF filtering enhances low-dose dynamic CT for breast cancer assessment.
Findings
4D-SF significantly improves signal-to-noise and contrast-to-noise ratios in breast CT images.
4D-SF increases overall image quality and tumor margin sharpness according to observer evaluations.
4D-SF improves correlation between tumor size on CT and pathological specimens.
Abstract
To evaluate the effects of four-dimensional noise reduction filtering using a similarity algorithm (4D-SF) on the image quality and tumor visibility of low-dose dynamic computed tomography (CT) in evaluating breast cancer. Thirty-four patients with 38 lesions who underwent low-dose dynamic breast CT and were pathologically diagnosed with breast cancer were enrolled. Dynamic CT images were reconstructed using iterative reconstruction alone or in combination with 4D-SF. We selected the peak enhancement phase image of breast cancer for each patient for quantitative and qualitative evaluations of image quality and measurement of the maximum diameter of breast cancer. The signal-to-noise and contrast-to-noise ratios were calculated for quantitative evaluation. The maximum diameters of the breast cancer were measured from the images obtained with and without 4D-SF (4D-SF ±) (size-4D-SF + and…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMedical Imaging Techniques and Applications · Radiation Dose and Imaging · Advanced X-ray and CT Imaging
