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

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 visualizatio...

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Publicado en:Journal of Digital Imaging Vol. 32; no. 2; pp. 300 - 314
Autores principales: Bandyopadhyay, Oishila, Biswas, Arindam, Bhattacharya, Bhargab B.
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Apr2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2019
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10278-018-0145-0
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        atl: Bone-Cancer Assessment and Destruction Pattern Analysis in Long-Bone X-ray Image.
      aug:
        au:
          Bandyopadhyay, Oishila
          Biswas, Arindam
          Bhattacharya, Bhargab B.
        affil: Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani, Kalyani, India
      sug:
        subj:
          Bone Neoplasms Diagnosis
          Neoplasm Staging Evaluation
          Neoplasm Grading Evaluation
          Bone and Bones Radiography
          Human
          Bone Neoplasms Analysis
          Bone and Bones Physiology
          Neoplasms Classification
          Digital Imaging
      ab: 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.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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