Three-dimensional geometry of a bone is important in the correct diagnosis
of a disease, arthritis, or other bone deformities. The modalities such as Computer
Tomography Scans and Magnetic Resonance Imaging are used for a three-dimensional
view of a bone. Both the above- stated modalities have high costs and expose the
patient to strong carcinogenic radiations. Computer Tomography captures an extensive
number of images to collect the required information from a bone. Another modality
Magnetic Resonance Imaging is more suitable for retrieving information from soft
tissues rather than bones. Therefore, it becomes less effective to read the pathology
from bones. This has motivated the authors to identify imaging techniques useful in
detecting the pathology or deformity in bones. Also, this is the need of the hour to
provide a low cost and safer technique of bone imaging. To address this need, we
present a review of the bone imaging techniques and techniques applied for the
conversion of two dimensional images into three-dimensional form. We also give the
directions for developing the patient-specific and organ-specific optimized techniques
for 3-D reconstruction.
Keywords: Dual-energy, Deep learning, Deformation, Femur, Machine learning, Three dimensional, X-ray.
