JOURNAL ARTICLE

Modified watershed technique and post-processing for segmentation of skin lesions in dermoscopy images

Hanzheng Wang, Randy H Moss, Xiaohe Chen, R Joe Stanley, William V Stoecker, M Emre Celebi, Joseph M Malters, James M Grichnik, Ashfaq A Marghoob, Harold S Rabinovitz, Scott W Menzies, Thomas M Szalapski
Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society 2011, 35 (2): 116-20
20970307
In previous research, a watershed-based algorithm was shown to be useful for automatic lesion segmentation in dermoscopy images, and was tested on a set of 100 benign and malignant melanoma images with the average of three sets of dermatologist-drawn borders used as the ground truth, resulting in an overall error of 15.98%. In this study, to reduce the border detection errors, a neural network classifier was utilized to improve the first-pass watershed segmentation; a novel "edge object value (EOV) threshold" method was used to remove large light blobs near the lesion boundary; and a noise removal procedure was applied to reduce the peninsula-shaped false-positive areas. As a result, an overall error of 11.09% was achieved.

Full Text Links

Find Full Text Links for this Article

Discussion

You are not logged in. Sign Up or Log In to join the discussion.

Related Papers

Remove bar
Read by QxMD icon Read
20970307
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"