Research Papers

Automated image analysis of digital colposcopy for the detection of cervical neoplasia

[+] Author Affiliations
Sun Young Park

University of Texas, Department of Biomedical Engineering, Austin, Texas 78712

Michele Follen

University of Texas, M. D. Anderson Cancer Center, Department of Biostatistics and Applied Mathematics and Department of Gynecologic Oncology, Center for Biomedical Engineering, Houston, Texas 77030

Andrea Milbourne, Helen Rhodes

University of Texas Health Science Center, Department of Gynecology, Obstetrics and Reproductive Sciences, Houston, Texas 77030

Anais Malpica

University of Texas, M. D. Anderson Cancer Center, Department of Pathology, Houston, Texas 77030

Nick MacKinnon, Calum MacAulay

British Columbia Cancer Center, Department of Optical Imaging and Gynecologic Oncology, Vancouver, British Columbia V5Z 1L3, Canada

Mia K. Markey

University of Texas, Department of Biomedical Engineering, Austin, Texas 78712

Rebecca Richards-Kortum

Rice University, Department of Bioengineering, Houston, Texas 77005

J. Biomed. Opt. 13(1), 014029 (January 16, 2008). doi:10.1117/1.2830654
History: Received February 28, 2007; Revised October 21, 2007; Accepted October 23, 2007; Published January 16, 2008
Text Size: A A A

Digital colposcopy is a promising technology for the detection of cervical intraepithelial neoplasia. Automated analysis of colposcopic images could provide an inexpensive alternative to existing screening tools. Our goal is to develop a diagnostic tool that can automatically identify neoplastic tissue from digital images. A multispectral digital colposcope (MDC) is used to acquire reflectance images of the cervix with white light before and after acetic-acid application in 29 patients. A diagnostic image analysis tool is developed to identify neoplasia in the digital images. The digital image analysis is performed in two steps. First, similar optical patterns are clustered together. Second, classification algorithms are used to determine the probability that these regions contain neoplastic tissue. The classification results of each patient’s images are assessed relative to the gold standard of histopathology. Acetic acid induces changes in the intensity of reflected light as well as the ratio of green to red reflected light. These changes are used to differentiate high-grade squamous intraepithelial (HGSIL) and cancerous lesions from normal or low-grade squamous intraepithelial (LGSIL) tissue. We report diagnostic performance with a sensitivity of 79% and a specificity of 88%. We show that diagnostically useful digital images of the cervix can be obtained using a simple and inexpensive device, and that automated image analysis algorithms show a potential to identify histologically neoplastic tissue areas.

Figures in this Article
© 2008 Society of Photo-Optical Instrumentation Engineers

Citation

Sun Young Park ; Michele Follen ; Andrea Milbourne ; Helen Rhodes ; Anais Malpica, et al.
"Automated image analysis of digital colposcopy for the detection of cervical neoplasia", J. Biomed. Opt. 13(1), 014029 (January 16, 2008). ; http://dx.doi.org/10.1117/1.2830654


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement


  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.