casa 18(15): e2

Research Article

Pancreas Contour Detection Based On Shearlet Domain In Low Quality Medical Images

Download153 downloads
  • @ARTICLE{10.4108/eai.18-6-2018.156319,
        author={Nguyen Thanh Binh and Nguyen Mong Hien and Pham Bao Quoc and Vo Thi Hong Tuyet},
        title={Pancreas Contour Detection Based On Shearlet Domain In Low Quality Medical Images},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={5},
        number={15},
        publisher={EAI},
        journal_a={CASA},
        year={2018},
        month={12},
        keywords={B-spline, shearlet transform, low quality image, pancreas detection},
        doi={10.4108/eai.18-6-2018.156319}
    }
    
  • Nguyen Thanh Binh
    Nguyen Mong Hien
    Pham Bao Quoc
    Vo Thi Hong Tuyet
    Year: 2018
    Pancreas Contour Detection Based On Shearlet Domain In Low Quality Medical Images
    CASA
    EAI
    DOI: 10.4108/eai.18-6-2018.156319
Nguyen Thanh Binh1,*, Nguyen Mong Hien1,2, Pham Bao Quoc1, Vo Thi Hong Tuyet3
  • 1: Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology, VNU-HCM, Vietnam
  • 2: Faculty of Engineering and Technology, Tra Vinh University, Vietnam
  • 3: Faculty of Information Technology, Ho Chi Minh City Open University, Vietnam
*Contact email: ntbinh@hcmut.edu.vn

Abstract

Medical images are very useful in diagnosis and treatment. The low quality medical image will be difficult for the doctor to find abnormalities in the image. One of the difficulties for the doctor is how to clarify parts of the medical image, especially the pancreas. In this paper, we propose the new method for object contour detection based on context awareness in low quality medical images in shearlet domain. The object in medical images which detect contour here is pancreas object. The proposed method includes two periods: improving the medical image quality and detecting pancreas contour. To evaluate the results of the proposed method, we compared the result with the recent methods.