Segmentation is a very common task in image analysis and consists in extracting the contours of a structure of interest in the image. ImFusion Suite and ImFusion Labels help users segment any organ, from manual labeling of 2D and 3D data sets to (semi-)automatic segmentation of any anatomy in 2D and 3D and a tight integration with machine learning modules.
ImFusion Suite and ImFusion Labels also include algorithms designed to automatically enhance and refine existing segmentations. These algorithms can be utilized to improve segmentations generated by other software tools or through manual annotation processes. In the figure herebelow, we show the refinement of a femur segmentation in a CT volume using image matting.
Each segmentation problem exhibits unique characteristics, such as prior knowledge regarding appearance and shape. Consequently, segmentation algorithms need to be customized to ensure robustness. Therefore, our portfolio includes a variety of specialized algorithms, as illustrated in the figures below.