Automated follicle analysis in ovarian ultrasound

Anthony Krivanek; Weidong Liang; Gordon E. Sarty; Roger A. Pierson; Milan Sonka

doi:10.1117/12.310937

24 June 1998 Automated follicle analysis in ovarian ultrasound

Anthony Krivanek, Weidong Liang, Gordon E. Sarty, Roger A. Pierson, Milan Sonka

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310937
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

For women undergoing assisted reproductive therapy, ovarian ultrasound has become an invaluable tool for monitoring the growth and assessing the physiological status of individual follicles. Measurements of the size and shape of follicles are the primary means of evaluation by physicians. Currently, follicle wall segmentation is achieved by manual tracing which is time consuming and susceptible to inter- operator variation. We are introducing a completely automated method of follicle wall isolation which provides faster, more consistent analysis. Our automated method is a 4-step process which employs watershed segmentation and a knowledge-based graph search algorithm which utilizes a priori information about follicle structure for inner and outer wall detection. The automated technique was tested on 36 ultrasonographic images of woman's ovaries. Five images from this set were omitted due to poor image quality. Validation of the remaining 31 ultrasound images against manually traced borders has shown an average rms error of 0.61 +/- 0.40 mm for inner border and 0.61 +/- 0.31 mm for outer border detection. Quantitative comparison of the computer-defined borders and the user-defined borders advocates the accuracy of our automated method of follicle analysis.

Citation Download Citation

Anthony Krivanek, Weidong Liang, Gordon E. Sarty, Roger A. Pierson, and Milan Sonka "Automated follicle analysis in ovarian ultrasound", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310937

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available