4 citations · 4 across the 3 of their papers we have counts for
3 papers
Generation of Chest CT pulmonary Nodule Images by Latent Diffusion Models using the LIDC-IDRI Dataset
Kaito Urata, Maiko Nagao, Atsushi Teramoto +3
Recently, computer-aided diagnosis systems have been developed to support diagnosis, but their performance depends heavily on the quality and quantity of training data. However, in…
Visual question answering-based image-finding generation for pulmonary nodules on chest CT from structured annotations
Maiko Nagao, Kaito Urata, Atsushi Teramoto +3
Interpretation of imaging findings based on morphological characteristics is important for diagnosing pulmonary nodules on chest computed tomography (CT) images. In this study, we…
Automated Description Generation of Cytologic Findings for Lung Cytological Images Using a Pretrained Vision Model and Dual Text Decoders: Preliminary Study
Atsushi Teramoto, Ayano Michiba, Yuka Kiriyama +3
Objective: Cytology plays a crucial role in lung cancer diagnosis. Pulmonary cytology involves cell morphological characterization in the specimen and reporting the corresponding f…