Method, apparatus, electronic device, and medium for generating image

A method for training a model, wherein the model comprises:

• a first feature extraction model configured to extract, from functional magnetic resonance imaging (fMRI) data, a first feature map of the fMRI data, the first feature map being multidimensional data having a temporal dimension related to a sample collection time of the fMRI data;
• a first conversion model configured to convert the first feature map based on the temporal dimension, the first conversion model comprising a first attention model;
• a second feature extraction model configured to extract, from electroencephalogram (EEG) data, a second feature map of the EEG data, the second feature map being multidimensional data having a spatial dimension related to an electrode for collecting the EEG data;
• a second conversion model configured to convert the second feature map based on the spatial dimension, the second conversion model comprising a second attention model;
• and a generation model configured to generate an image based on the converted first feature map and the converted second feature map,
• and the method comprises:
• generating a training dataset;
• and
• updating the model based on the training dataset,
• wherein the training dataset comprises:
• a first target image and first fMRI data and first EEG data corresponding to the first target image;
• a second target image and second fMRI data and second EEG data corresponding to the second target image;
• and
• a third target image and third fMRI data and third EEG data corresponding to the third target image, wherein the third target image is a spatial combination of the first target image and the second target image.

An apparatus for generating an image from functional magnetic resonance imaging (fMRI) data and electroencephalogram (EEG) data, comprising:

• a first feature extraction unit configured to extract a first feature map of the fMRI data, the first feature map being multidimensional data having a temporal dimension related to a sample collection time of the fMRI data;
• a first conversion unit configured to convert the first feature map based on the temporal dimension of the first feature map and a first attention model;
• a second feature extraction unit configured to extract a second feature map of the EEG data, the second feature map being multidimensional data having a spatial dimension related to an electrode for collecting the EEG data;
• a second conversion unit configured to convert the second feature map based on the spatial dimension of the second feature map and a second attention model;
• and
• a generation unit configured to generate an image based on the converted first feature map and the converted second feature map.