Abstract: The present disclosure discloses a method and apparatus for analyzing medical image. A specific embodiment of the method includes: acquiring medical image data; generating multi-scale decision sample data based on the medical image data; inputting the multi-scale decision sample data into a deep neural network model to obtain an auxiliary diagnosis data of the medical image, the deep neural network model being trained according to a consistency principle between multi-scale training sample data and an output result of the deep neural network model. In the embodiment, a multi-scale training sample is used to accelerate the training process of the deep neural network model, thus the auxiliary diagnosis decision process can be accelerated, while the accuracy of the trained deep neural network model of the embodiment is improved according to a consistency principle of data between different scales and output results, thereby improving the accuracy of auxiliary diagnosis decision.

Abstract: An embodiment of the present disclosure discloses a method and apparatus for annotating a medical image. An embodiment of the method comprises: acquiring a to-be-annotated medical image; annotating classification information for the to-be-annotated medical image, wherein the classification information comprises a category of a diagnosis result and a grade of the diagnosis result corresponding to the medical image; processing the to-be-annotated medical image using a pre-trained lesion area detection model, framing a lesion area in the to-be-annotated medical image, and annotating a lesion type of the lesion area, to enable the to-be-annotated medical image to be annotated with the lesion area and the lesion type of the lesion area; and splitting the framed lesion area from the to-be-annotated medical image with the framed lesion area to form a split image of the to-be-annotated medical image, to enable the to-be-annotated medical image to be annotated with the split image.

Abstract: A method and system for image processing is provided. The technique includes acquiring data related to the processing, performing a pre-processing of the data, performing a segmentation of a subject, performing a post-processing of the result of the segmentation and managing storage of the data. The post-process includes a calibrating and a rendering of the data.

Abstract: An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

Abstract: Methods and systems for detecting and defeating a low and slow application DDoS attack, comprising: computing the Entropy of a plurality of detectors, at least in part selected from a group Geo detector, a group response size detector, a group preference detector, and an individual client behavior detector, wherein the plurality of detectors each describe a feature of traffic affected by the DDoS attack; composing the plurality of detectors on one or more of a Receiver Operating Characteristic (ROC) curve basis and a correlation basis; and implementing a countermeasure to mitigate the DDoS attack.

Abstract: A method and system for image processing is provided. The technique includes acquiring data related to the processing, performing a pre-processing of the data, performing a segmentation of a subject, performing a post-processing of the result of the segmentation and managing storage of the data. The post-process includes a calibrating and a rendering of the data.

Abstract: The present invention relates to a system and method for image processing. An image data processing system is disclosed comprising an image cutting engine for image cutting based on image data; a region of interest processing engine for selecting at least a rendering method for a region of interest; a processing engine for adjusting sampling rate; and rendering engine for rendering the image, with the rendering method selected by the region of interest processing engine. More particularly, the present invention relates to image processing techniques that perform image manipulation, volume rendering, displaying targeted regions of interest and other related functions.