Bone-Cancer Assessment and Destruction Pattern Analysis in Long-Bone X-ray Image

Abstract

Bone cancer originates from bone and rapidly spreads to the rest of the body affecting the patient. A quick and preliminary diagnosis of bone cancer begins with the analysis of bone X-ray or MRI image. Compared to MRI, an X-ray image provides a low-cost diagnostic tool for diagnosis and visualization of bone cancer. In this paper, a novel technique for the assessment of cancer stage and grade in long bones based on X-ray image analysis has been proposed. Cancer-affected bone images usually appear with a variation in bone texture in the affected region. A fusion of different methodologies is used for the purpose of our analysis. In the proposed approach, we extract certain features from bone X-ray images and use support vector machine (SVM) to discriminate healthy and cancerous bones. A technique based on digital geometry is deployed for localizing cancer-affected regions. Characterization of the present stage and grade of the disease and identification of the underlying bone-destruction pattern are performed using a decision tree classifier. Furthermore, the method leads to the development of a computer-aided diagnostic tool that can readily be used by paramedics and doctors. Experimental results on a number of test cases reveal satisfactory diagnostic inferences when compared with ground truth known from clinical findings. Keywords Bone cancer • Bone X-ray • Connected component • Decision tree • Ortho-convex cover • Runs-test • Support vector machine Oishila Bandyopadhyay

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“…By integrating several classifiers, the method achieved accurate decisions regarding a bone-destruction pattern, stage, and grade of cancer in 85% of cases. 42 …”

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“…ROI, region of interest; SVM, support vector machine. (Reprinted with permission from Springer Nature; J Digit Imaging 2019;32:300-313, Bandyopadhyay et al 19 ) encountered pathologies. The described system uses radiograph image features as well as semantic terms, integrates user feedback to refine subsequent searches, and is able to predict semantic features for the query image.…”

miRNA-128 modulates bone neoplasms cells proliferation and migration through the WNT/β-catenin and EMT signal pathways

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