2results about How to "Has reference value" patented technology

The application discloses a lung nodule growth prediction method based on combination of LSTM and GAN, relates to the technical field of image analysis and processing, and comprises the following steps: collecting multi-time chest CT data, performing labeling and auditing to form a data set; performing pretreatment on the labeled CT data to obtain standardized lung nodule ROIs; segmenting out lung nodule regions by using a three-dimensional image segmentation network to generate three-dimensional segmentation masks; inputting the segmentation masks of multiple time nodes into an LSTM network to extract time sequence feature vectors representing dynamic evolution of the nodule; based on the time sequence feature vectors and random noise, a generator synthesizes predicted lung nodule images at future time points, and a discriminator optimizes model parameters by joint optimization of multiple loss functions; and inputting three-dimensional segmentation masks at the current and historical time points to generate predicted lung nodule images at future time points. The application can effectively improve the situation that the prior art is insufficient in utilization of time sequence information and lacks high-quality generation and inference capability.

The present disclosure relates to the technical field of endoscopy, and provides a path planning method. In the method, a cross-sectional image of a target object and hardware parameters of a bronchoscope robot corresponding to the target object are obtained; according to the cross-sectional image of the target object, lesion feature information, trachea feature information and blood vessel feature information of the target object are determined; according to the hardware parameters of the bronchoscope robot, and the lesion feature information, the trachea feature information and the blood vessel feature information of the target object, an airway wall puncture biopsy path of the bronchoscope robot is determined. In this way, since multiple constraint conditions are considered in the generation process of the airway wall puncture biopsy path, the most efficient and safe airway wall puncture biopsy path can be obtained, thereby the problems of subjectivity and human error that occur when a scheme is artificially formulated can be avoided, and thus the airway wall puncture biopsy path obtained by the embodiment is more accurate and has more reference value, and the safety and efficiency of the puncture biopsy are also improved.