Abstract: A method for enhancing an accuracy of a benign tumor development trend assessment system includes: a first processing procedure, an image captured before the treatment is inputted to and be processed by a server computing device of the benign tumor development trend assessment system to obtain a first processing result; a second processing procedure, the images captured before and in at least one period after the treatment are inputted to and processed by the server computing device to obtain a second processing result; a trend analyzing procedure, the trend analyzing module of the server computing device analyzes the first processing result, the second processing result and the trend pathways to obtain a tumor development trend result; and a storing procedure, the first processing result, the second processing result and the tumor development trend result are transformed to an individual trend pathway which is stored in the trend analyzing module.

Abstract: An apparatus for medical graphics edition includes a display device, an electronic calculator, and a medical graphics editor. The display device displays at least one medical image, and the medical graphics editor is executed by the electronic calculator. The medical graphics editor includes a shaping tool, which is used to shape a contour in the medical image. The shaping tool includes at least one shaping pattern and a shaping vector pattern. The shaping vector pattern is combined with the shaping pattern to form a pattern of the shaping tool. The shaping tool is to cause the contour, based on the shaping pattern, to have a shape change in a proportion in the direction indicated by the shaping vector pattern. In addition, the medical graphics editor further includes a scaling tool.

Abstract: A medical information processing method, which is used to process medical information including descriptive information and to-be-processed data. The processed medical information conforms a calculation of a medical information calculation application. The method includes a calculation required information detection process and a verification information generation process. The calculation required information detection process detects at least one calculation required information required by the medical information calculation application from the descriptive information, if the detection result is true, deletes all or part of accompanying descriptive information other than the calculation required information, and generates to-be-processed medical information based on the to-be-process data and the remained descriptive information.

Abstract: A brain tumor types distinguish system includes an image outputting device and a server computing device. The image outputting device outputs at least three brain images captured from the position of a brain tumor. The server computing device pre-stores a plurality of distinguish pathways corresponding to different types of brain tumors. The server computing device includes an image receiving module, an image pre-processing module, a data comparison module and a distinguish module. The image receiving module receives the brain images. The image pre-processing module pre-processes the brain images to obtain corresponding processed images thereof. The data comparison module compares the brain images and the processed images with the distinguish pathways to obtain at least three comparison results. The distinguish module statistically analyzes the comparison results to obtain a distinguish result.

Abstract: A benign tumor development trend assessment system includes an image outputting device and a server computing device. The image outputting device outputs first/second images captured from the same position in a benign tumor. The server computing device includes an image receiving module, an image pre-processing module, a target extracting module, a feature extracting module and a trend analyzing module. The image receiving module receives the first/second images. The image pre-processing module pre-processes the first/second images to obtain first/second local images. The target extracting module automatically detects and delineates tumor regions from the first/second local images to obtain first/second region of interest (ROI) images. The feature extracting module automatically identifies the first/second ROI images to obtain at least one first/second features. The trend analyzing module analyzes the first/second features to obtain a tumor development trend result.

Abstract: A method for enhancing an accuracy of a benign tumor development trend assessment system includes: a first processing procedure, an image captured before the treatment is inputted to and be processed by a server computing device of the benign tumor development trend assessment system to obtain a first processing result; a second processing procedure, the images captured before and in at least one period after the treatment are inputted to and processed by the server computing device to obtain a second processing result; a trend analyzing procedure, the trend analyzing module of the server computing device analyzes the first processing result, the second processing result and the trend pathways to obtain a tumor development trend result; and a storing procedure, the first processing result, the second processing result and the tumor development trend result are transformed to an individual trend pathway which is stored in the trend analyzing module.

Abstract: A benign tumor development trend assessment system includes an image outputting device and a server computing device. The image outputting device outputs first/second images captured from the same position in a benign tumor. The server computing device includes an image receiving module, an image pre-processing module, a target extracting module, a feature extracting module and a trend analyzing module. The image receiving module receives the first/second images. The image pre-processing module pre-processes the first/second images to obtain first/second local images. The target extracting module automatically detects and delineates tumor regions from the first/second local images to obtain first/second region of interest (ROI) images. The feature extracting module automatically identifies the first/second ROI images to obtain at least one first/second features. The trend analyzing module analyzes the first/second features to obtain a tumor development trend result.