3 results about "T1 weighted" patented technology

The application relates to an ultrasound sound velocity image generation method and system based on a T1 weighted MRI image, and the method comprises the following steps: acquiring a T1 weighted MRI image and a CT image of a historical subject as sample data; a deep learning model is constructed, the deep learning model comprises a first stage network and a second stage network; the first stage network is trained through the sample data, so that the first stage network generates a CT image when a T1 weighted MRI image is input; the second stage network is trained through the sample data and the CT image generated by the first stage network, so that the second stage network generates an ultrasound sound velocity image when a T1 weighted MRI image and a CT image are input. The technical scheme can effectively generate a high-quality ultrasound sound velocity image, avoids ionizing radiation caused by CT scanning, and can be used for planning regulation of ultrasound energy in sonodynamic therapy, so that the accuracy and efficiency of treatment are improved.

The application belongs to the field of image segmentation, and relates to a lateral ventricle choroid plexus segmentation and quantification method based on enhanced T1 weighted magnetic resonance images, S1: obtaining brain enhanced T1 weighted magnetic resonance images and performing pretreatment to obtain standardized brain images; S2: based on the standardized brain images, combining a preset enhancement intensity threshold and a lateral ventricle anatomical position constraint, constructing a choroid plexus candidate region; S3: using a trained choroid plexus segmentation model to perform feature discrimination and segmentation on the choroid plexus candidate region to generate an initial segmentation mask; S4: performing post-processing optimization on the initial segmentation mask to remove false positive regions to obtain a final lateral ventricle choroid plexus segmentation mask; and S5: based on the final lateral ventricle choroid plexus segmentation mask, performing choroid plexus quantification parameter calculation. The problems of low segmentation precision, poor integrity and insufficient stability are solved.

The application discloses a kind of infant brain white matter injury cognitive prognosis evaluation method, system and device, it is related to medical technical field, the method includes obtaining the T1 weighted imaging and diffusion tensor image of the brain of infant to be evaluated;The local white matter injury area is outlined on T1 weighted image, and binary individual lesion mask is generated;The diffusion tensor image is preprocessed, and partial anisotropy map is generated;Based on individual lesion mask and diffusion tensor image, the lesion volume involving fiber bundle and white matter structure disconnection score are calculated in parallel;The lesion volume involving fiber bundle and white matter structure disconnection score are input into pre-trained decision tree model, according to the preset determination rule, the evaluation result of the risk of infant cognitive development delay is output;The method provides new quantitative index for PWML dominant lesion, can be derived to conventional MRI image and analyzed, without acquiring DTI data, and provides a new solution for early evaluation of prognosis.