摘要:
The invention relates to a method and an according apparatus and system for labeling one or more parts of a spine in at least one magnetic resonance (MR) image (30) of a human or animal body, said method comprising the following steps: transforming the image (30) having a first number of intensity levels into a target image (33) having a second number of intensity levels, the second number of intensity levels being smaller than the first number of intensity levels, by considering the entropy of texture variations in one or more training images; determining a position, in particular a center position, in each of the one or more parts of the spine in the target image (33); and labeling the determined position of the one or more parts of the spine in the image (30) or the target image (33) with anatomical labels.
摘要:
A pipe-line method for multi-label segmentation of anatomic structures in a medical image by means of a convolutional neural network trained with a weighted loss function that takes into account under-representation of at least one anatomical structure in the ground-truth mask relative to other anatomical structures. Different architectures for the convolutional neural network are described.
摘要:
The invention relates to a method and an according apparatus and system for segmentation of anatomical structures in medical images, wherein an anatomical structure represented in a medical image is segmented by applying an algorithm based on a morphological active contour without edges (MACWE) to the medical image, wherein in the algorithm based on the morphological active contour without edges one or more features relating to a surrounding and/or context of the anatomical structure represented in the medical image are considered.
摘要:
The invention relates to a method and an according apparatus and system for analyzing medical images of blood vessels, said method comprising the following steps: a) classifying a surrounding of at least one vessel represented in at least one medical image by applying a first classifier to the medical image, whereby the surrounding of the vessel is assigned to one of at least two surrounding classes, and b) segmentation of the at least one vessel dependent on the surrounding class to which the surrounding of the vessel has been assigned. The invention allows for a reliable segmentation and/or shape detection, in particular bifurcation detection, of blood vessels represented in medical images.