Abstract: The present disclosure relates to an image registration method and a model training method thereof. The image registration method comprises obtaining a reference image and a floating image to be registered, performing image preprocessing on the reference image and the floating image, performing non-rigid registration on the preprocessed reference image and floating image to obtain a registration result image, and outputting the registration result image. The image preprocessing comprises performing, on the reference image and the floating image, coarse-to-fine rigid registration based on iterative closest point registration and mutual information registration. The non-rigid registration uses a combination of a correlation coefficient and a mean squared error between the reference image and the registration result image as a loss function.

Abstract: The present disclosure relates to a method, a system, and a storage medium for segmenting a lung image. The method for segmenting a lung image comprises: obtaining medical image data containing a lung region; performing lung lobe segmentation on the medical image data to generate a plurality of lung lobe data subsets; generating updated lung image data based on one or a plurality of lung lobe data subsets in the plurality of lung lobe data subsets; and performing nidus segmentation on the updated lung image data to generate a segmentation image that identifies a pneumonia nidus.

Abstract: A mechanical-model based earthquake-induced landslide hazard assessment method in earthquake-prone mountainous area includes: obtaining the cohesion and internal friction angle through a geological map of the study area and a geotechnical physical parameter; obtaining simulated ground motions by combining a pulse-like ground motion effect model and a pulse-like ground motion response model; calculating slope permanent displacement according to the simulated ground motions, the cohesion, the internal friction angle and other parameters; obtaining a statistical relationship between the permanent displacement and a landslide probability according to permanent displacement data derived from historical earthquake-induced landslides and historical strong earthquake records; and predicting earthquake-induced landslide probability according to the slope permanent displacement and the statistical relationship between the permanent displacement and the landslide probability, and quantitatively evaluating earthquake-ind

Abstract: A mechanical-model based earthquake-induced landslide hazard assessment method in earthquake-prone mountainous area includes: obtaining the cohesion and internal friction angle through a geological map of the study area and a geotechnical physical parameter; obtaining simulated ground motions by combining a pulse-like ground motion effect model and a pulse-like ground motion response model; calculating slope permanent displacement according to the simulated ground motions, the cohesion, the internal friction angle and other parameters; obtaining a statistical relationship between the permanent displacement and a landslide probability according to permanent displacement data derived from historical earthquake-induced landslides and historical strong earthquake records; and predicting earthquake-induced landslide probability according to the slope permanent displacement and the statistical relationship between the permanent displacement and the landslide probability, and quantitatively evaluating earthquake-ind