Shu Zama, Tomoyuki Fujioka, Emi Yamaga, Kazunori Kubota, Mio Mori, Leona Katsuta, Yuka Yashima, Arisa Sato, Miho Kawauchi, Subaru Higuchi, Masaaki Kawanishi, Toshiyuki Ishiba, Goshi Oda, Tsuyoshi Nakagawa, Ukihide Tateishi
BACKGROUND AND OBJECTIVES: This study compares the clinical properties of original breast ultrasound images and those synthesized by a generative adversarial network (GAN) to assess the clinical usefulness of GAN-synthesized images. MATERIALS AND METHODS: We retrospectively collected approximately 200 breast ultrasound images for each of five representative histological tissue types (cyst, fibroadenoma, scirrhous, solid, and tubule-forming invasive ductal carcinomas) as training images...
December 21, 2023: Medicina