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Prostate boundary segmentation from 2D ultrasound images
Author(s) -
Ladak Hanif M.,
Mao Fei,
Wang Yunqiu,
Downey Dónal B.,
Steinman David A.,
Fenster Aaron
Publication year - 2000
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.1286722
Subject(s) - initialization , computer science , artificial intelligence , segmentation , interpolation (computer graphics) , computer vision , pixel , image segmentation , medical imaging , active contour model , boundary (topology) , image (mathematics) , mathematics , mathematical analysis , programming language
Outlining, or segmenting, the prostate is a very important task in the assignment of appropriate therapy and dose for cancer treatment; however, manual outlining is tedious and time‐consuming. In this paper, an algorithm is described for semiautomatic segmentation of the prostate from 2D ultrasound images. The algorithm uses model‐based initialization and the efficient discrete dynamic contour. Initialization requires the user to select only four points from which the outline of the prostate is estimated using cubic interpolation functions and shape information. The estimated contour is then deformed automatically to better fit the image. The algorithm can easily segment a wide range of prostate images, and contour editing tools are included to handle more difficult cases. The performance of the algorithm with a single user was compared to manual outlining by a single expert observer. The average distance between semiautomatically and manually outlined boundaries was found to be less than 5 pixels (0.63 mm), and the accuracy and sensitivity to area measurements were both over 90%.