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We adopted the simple FPM for tissue classification where each feature was treated individually.
Nodes are colored according to tissue classification.
Tissue classification by examining sets of ultrasound parameters is an elusive goal.
However, any statistical or machine learning classifier could be used in combination with a set of hand-crafted features for tissue classification.
We addressed the tissue classification task through a learned feature approach instead of a hand-crafted feature approach13,17,27,29,38,42.
The algorithm is evaluated for the case of liver tissue classification.
The paper also systematically explains and presents approaches for training and validating DL classifiers for a number of image-based problems in digital pathology, including cell detection, segmentation and tissue classification.
The HR-pQCT scans were analysed using a new method developed for this study: high resolution tissue classification (HRTC).
The algorithm is aimed at aiding in visual tissue classification and texture-based visual tissue tracking in echocardiographic images.
The tools include skull and scalp removal, image nonuniformity compensation, voxel-based tissue classification, topological correction, rendering, and editing functions.
By utilizing the low-frequency characteristic of shading distribution, we first generate a "shading-free" template image by enforcing uniformity on CBCT voxels of the same tissue type via a technique named partitioned tissue classification.
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