6 results about "Bone imaging" patented technology

This application discloses a method, display method, apparatus, device, and storage medium for determining jawbone features. The method includes: obtaining a radicular bone scan image; segmenting the jawbone based on the radicular bone scan image to determine a segmented jawbone image; using a neural network, taking both the radicular bone scan image and the segmented jawbone image representing the same jawbone location as input, to determine a jawbone feature image and a cancellous bone feature image; comparing the jawbone feature image and the cancellous bone feature image, and determining a cortical bone feature image based on the differences; and determining and outputting cortical bone feature information based on the cortical bone feature image. The method provided in this application can improve the accuracy and efficiency of jawbone feature determination.

This invention provides a method, system, electronic device, and storage medium for displaying images of bone grinding states, relating to the field of image processing technology. It includes: establishing a three-dimensional model of a target bone based on a user's bone scan image, and obtaining the three-dimensional model data of the target bone; determining the position information of a first target registration point in the camera coordinate system of a surgical robot; determining an initial registration matrix based on the position information and the three-dimensional model data; determining a secondary registration matrix based on the initial registration matrix and a second target registration point, to obtain a target pose matrix based on the secondary registration matrix; transforming the bone prosthesis model into the coordinate system of the three-dimensional model of the target bone based on the pose matrix of the bone prosthesis model; determining the grinding state of the target grinding point in the coordinate system of the three-dimensional model based on the distance from the target grinding point on the three-dimensional model to the bone prosthesis model; and displaying the target grinding point on the three-dimensional model with a preset color corresponding to the grinding state.

This application discloses a tooth segmentation method, display method, apparatus, device, and storage medium. The tooth segmentation method includes: obtaining a root bone scan image; inputting the root bone scan image into a localization model to obtain first localization information for N teeth, the first localization information being used to determine the position information of the teeth in the root bone scan image; identifying the center information of different teeth in the root bone scan image to obtain second localization information for M teeth; N and M are positive integers greater than 1; determining the region of interest for tooth segmentation based on the first localization information of the N teeth and the second localization information of the M teeth; and inputting the image corresponding to the segmented region of interest into the segmentation model to obtain the tooth segmentation result. The tooth segmentation method provided in this application balances comprehensiveness and accuracy in segmentation.

Embodiments of the present application provide a classification model training method, an image classification method, a computing device, a computer readable storage medium and a computer program product. The classification model training method comprises: obtaining a pre-training image dataset; pre-training a shallow network and a deep network of a to-be-trained classification model using the pre-training image dataset to obtain a first classification model after pre-training; obtaining a SPECT bone imaging dataset and generating an expanded dataset based on the SPECT bone imaging dataset using an image generation technology; inputting the SPECT bone imaging dataset into the first classification model to train the deep network of the first classification model using the SPECT bone imaging dataset to obtain a second classification model; combining the SPECT bone imaging dataset and the expanded dataset into a synthetic dataset, and adjusting network parameters of the second classification model using the synthetic dataset to obtain a target classification model after training. The technical solution provided by the embodiments of the present application improves the classification accuracy.

The present application discloses a root-bone feature determination method, a display method, an apparatus, a device, and a storage medium. The method comprises: obtaining a root-bone scan image; on the basis of the root-bone scan image, performing jawbone segmentation to determine a jawbone segmentation image; determining cortical bone feature information on the basis of the jawbone segmentation image; inputting the root-bone scan image into a localization model to obtain first localization information of N teeth, the first localization information being used for determining position information of the teeth in the root-bone scan image; identifying center information of different teeth in the root-bone scan image to obtain second localization information of M teeth, wherein N and M are positive integers greater than 1; obtaining a tooth segmentation result on the basis of the first localization information of the N teeth and the second localization information of the M teeth; and determining root-bone feature information on the basis of the cortical bone feature information and the tooth segmentation result. The method provided in the present application can improve the accuracy of root-bone feature determination.

This application relates to systems and methods for automated and interactive analysis of bone scan images to detect metastases. Presented herein are systems and methods that provide improved computer-aided display and analysis of nuclear medicine images. In particular, in certain embodiments, the systems and methods described herein provide improvements to a number of image processing steps for automated analysis of bone scan images to assess the cancer status of a patient. For example, improved methods are provided for image segmentation, hot spot detection, automated classification of hot spots as indicative of metastases, and calculation of risk indices such as bone scan index (BSI) values.