Disease Prediction using Machine Learning, Deep Learning and Data Analytics

Role of Artificial Intelligence in 3-D Bone Image Reconstruction: A Review

Author(s): Nitesh Pradhan, Vijaypal Singh Dhaka, Geeta Rani and Monika Agarwal

Pp: 17-30 (14)

DOI: 10.2174/9789815179125124010007

* (Excluding Mailing and Handling)


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.

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