Unveiling the future of breast cancer assessment: a critical review on generative adversarial networks in elastography ultrasound.

ABSTRACT: Elastography Ultrasound provides elasticity information of the tissues, which is crucial for understanding the density and texture, allowing for the diagnosis of different medical conditions such as fibrosis and cancer. In the current medical imaging scenario, elastograms for B-mode Ultrasound are restricted to well-equipped hospitals, making the modality unavailable for pocket ultrasound. To highlight the recent progress in elastogram synthesis, this article performs a critical review of generative adversarial network (GAN) methodology for elastogram generation from B-mode Ultrasound images. Along with a brief overview of cutting-edge medical image synthesis, the article highlights the contribution of the GAN framework in light of its impact and thoroughly analyzes the results to validate

SUBMITTER: Ansari MY 

PROVIDER: S-EPMC10731303 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature