Is image-to-image translation the panacea for multimodal image registration? A comparative study.

ABSTRACT: Despite current advancement in the field of biomedical image processing, propelled by the deep learning revolution, multimodal image registration, due to its several challenges, is still often performed manually by specialists. The recent success of image-to-image (I2I) translation in computer vision applications and its growing use in biomedical areas provide a tempting possibility of transforming the multimodal registration problem into a, potentially easier, monomodal one. We conduct an empirical study of the applicability of modern I2I translation methods for the task of rigid registration of multimodal biomedical and medical 2D and 3D images. We compare the performance of four Generative Adversarial Network (GAN)-based I2I translation methods and one contrastive representation learnin

SUBMITTER: Lu J 

PROVIDER: S-EPMC9704666 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature