Pix2Pix generative-adversarial network in improving the quality of T2-weighted prostate magnetic resonance imaging: a multi-reader study
This study critically assesses the efficacy of the Pix2Pix generative-adversarial network in enhancing T2W prostate MRI quality, demonstrating its potential to produce high-quality, realistic images indistinguishable from originals, thereby potentially advancing radiology practice by improving diagnostic accuracy and image reliability.
Authors
- Yeliz Başar (ORCID: https://orcid.org/0000-0002-1321-3617)
- Mustafa Ege Şeker (ORCID: https://orcid.org/0000-0001-7664-5786)
- Müjgan Orman (ORCID: https://orcid.org/0000-0002-9629-0211)
- Deniz Alış (ORCID: https://orcid.org/0000-0002-7045-1793)
- Ercan Karaarslan (ORCID: https://orcid.org/0000-0002-4581-4273)
- Mustafa Said Kartal (ORCID: https://orcid.org/0000-0002-0396-7183)
- Sabri Şirolu (ORCID: https://orcid.org/0000-0002-8443-0838)
- Aydan Arslan (ORCID: https://orcid.org/0000-0002-6073-1927)
- İlkay Öksüz (ORCID: https://orcid.org/0000-0001-6478-0534)
- Delal Şeker (ORCID: https://orcid.org/0000-0002-6863-7150)
- Serpil Kurtcan (ORCID: https://orcid.org/0000-0002-8207-0824)
- Nurper Denizoğlu (ORCID: https://orcid.org/0000-0002-3677-8872)
Institutions
- Dicle University (TR)
- Kent Hastanesi (TR)
- Acıbadem Adana Hospital (TR)
- Istanbul Technical University (TR)
Publication Details
- Journal
- Diagnostic and Interventional Radiology
- Published
- 2025-05-05
- DOI
- https://doi.org/10.4274/dir.2025.243102
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00