Method for increasing the robustness of computer-aided diagnosis to image processing uncertainties

摘要

A classifier (20) is trained by a feature matrix (18, 18′) made up of feature vectors (F11, . . . , Fkm). The feature vectors are generated by operating on each of a plurality (k) of training image data sets with each of a plurality (m) of image processing algorithms (121, . . . , 12m) to generate processed and segmented images. Features of the segmented regions are extracted (14) to generate the feature vectors. In this manner, the classifier is trained with data generated with a variety of image processing algorithms.

主权项

1. A system, comprising:
memory that stores computer readable instructions; a processor that executes the computer readable instructions stored in the memory, which causes the processor to:
process each of a plurality of training image data sets from a plurality of patients with known diagnoses with each of a plurality of image processing algorithms, wherein each of the training image datasets is processed with each of the plurality of image processing algorithms to produce a plurality of processed training images, and wherein each of the plurality of image processing algorithms produces one of the plurality of processed training images;extract features of the processed training images to generate feature vectors; andtrain a classifier with the generated feature vectors to recognize each known diagnosis of the known diagnoses.