BioMed Research International / 2021 / Article / Fig 1

Research Article

Using Machine Learning to Unravel the Value of Radiographic Features for the Classification of Bone Tumors

Figure 1

Examples of the features (upper panel) and scores depicting the presence or absence of sharp vs. ill-defined bone margins, geographic vs. moth-eaten vs. permeated pattern of bone destruction, and with vs. without expansive growth (lower panel) as seen on conventional radiographic images obtained from 3 patients. Patient A was an 8-year-old female with nonossifying fibroma. Patient B was a 34-year-old man with a giant cell tumor of bone, and Patient C was a 46-year-old woman with osteosarcoma.

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