Effectively Fine-tune to Improve Large Multimodal Models for Radiology Report Generation

no code implementations • 3 Dec 2023 • Yuzhe Lu, SungMin Hong, Yash Shah, Panpan Xu

Writing radiology reports from medical images requires a high level of domain expertise.

Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels

1 code implementation • 13 Dec 2021 • SungMin Hong, Anna K. Bonkhoff, Andrew Hoopes, Martin Bretzner, Markus D. Schirmer, Anne-Katrin Giese, Adrian V. Dalca, Polina Golland, Natalia S. Rost

However, multiple per-image annotations are often not available in a real-world application and the uncertainty does not provide full control on segmentation results to users.

Ensemble Learning Image Segmentation +3

3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images

1 code implementation • 20 Jul 2021 • SungMin Hong, Razvan Marinescu, Adrian V. Dalca, Anna K. Bonkhoff, Martin Bretzner, Natalia S. Rost, Polina Golland

Image synthesis via Generative Adversarial Networks (GANs) of three-dimensional (3D) medical images has great potential that can be extended to many medical applications, such as, image enhancement and disease progression modeling.

Generative Adversarial Network Image Enhancement +1