Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani, Kalyani, India.
Department of Information Technology, Indian Institute of Engineering Science and Technology, Shibpur, India.
J Digit Imaging. 2019 Apr;32(2):300-313. doi: 10.1007/s10278-018-0145-0.
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.
骨癌起源于骨骼，迅速扩散到身体的其他部位，影响患者。骨癌的快速初步诊断始于分析骨骼 X 射线或 MRI 图像。与 MRI 相比，X 射线图像为诊断和可视化骨癌提供了一种低成本的诊断工具。在本文中，提出了一种基于 X 射线图像分析的长骨癌症分期和分级评估的新技术。受癌症影响的骨骼图像通常在受影响区域显示骨骼纹理的变化。融合了不同的方法来进行我们的分析。在提出的方法中，我们从骨骼 X 射线图像中提取某些特征，并使用支持向量机 (SVM) 来区分健康和癌变的骨骼。基于数字几何的技术用于定位受癌症影响的区域。使用决策树分类器对疾病的当前阶段和等级进行特征描述，并识别潜在的骨骼破坏模式。此外，该方法还开发了一种计算机辅助诊断工具，便于护理人员和医生使用。与临床发现的已知真实情况相比，在许多测试案例上的实验结果表明，该方法可以得出令人满意的诊断推论。
