Research On Automatic Localization Of Anatomical Landmarks Of 3D Medical Image Based On Random Forest

In modern medicine,more and more three-dimensional medical images appear in the process of clinical diagnosis and treatment,and the automatic location of landmarks in three-dimensional medical images has become the key of medical image analysis tasks such as cephalometric analysis,prostate segmentation of CT images and so on.However,at present,the location of anatomic landmarks still depends on the manual measurement and location of doctors.This method not only wastes the time and energy of experienced doctors,but also affects the accuracy of location of anatomic landmarks due to different time states or differences between different doctors.Therefore,the positioning accuracy of anatomical landmarks directly affects the accuracy of follow-up medical image processing and analysis.Therefore,it has important clinical and theoretical value to develop the automatic location of anatomical landmarks in 3D medical images.Firstly,aiming at the problem of automatic location of anatomical landmarks in CBCT images,this paper proposes an automatic location method based on random forest.This method is divided into training stage and testing stage.In the training stage,firstly,the appearance features are extracted from the 3D medical image as the input of the first layer of random forest model,and the offset distance map of each anatomical landmark is generated by the random forest model.Then,the context feature is extracted from the offset distance map obtained in the previous step,and the context feature and the original appearance feature are combined as the input of the second layer of random forest to train the second layer of random forest.In the test stage,the CBCT image of the three-dimensional cephalometric measurement to be detected is input into the three-dimensional random forest model to obtain the offset distance map of the anatomical landmarks,and finally the coordinates of the anatomical landmarks are obtained by regression voting.The experimental results show that the method based on random forest can accurately locate the anatomical landmarks on the CBCT image.In this paper,aiming at the localization of anatomical landmarks in prostate CT images,a new algorithm based on random forest is proposed in.This method is divided into training stage and testing stage.In the training stage,the training data of prostate CT image is used as input to get the random forest model.In the testing stage,the model is applied to the test data of prostate CT image,and then the coordinates of anatomical landmarks of prostate CT image can be obtained.The experimental results show that this method can accurately locate the anatomical features of prostate CT images.