Using active contours and mathematical morphology tools for quantification of immunohistochemical images

被引：19
|
作者：
Elmoataz, A
Schüpp, S
Clouard, R
Herlin, P
Bloyet, D
机构：
[1] Inst Sci Mat & Rayonnement, GREYC, CNRS, UPRESA 6072, F-14050 Caen, France
[2] Ctr Francois Baclesse, Anat Pathol Lab, F-14021 Caen, France
来源：
SIGNAL PROCESSING | 1998年 / 71卷 / 02期
关键词：
Active contours; Mathematical morphology; Medical images; Segmentation;
D O I：
10.1016/S0165-1684(98)00146-7
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An image segmentation method is proposed, which combines mathematical morphology tools and active contours in two stages. First, contours are coarsely approximated by means of morphological operators. Second, these initial contours evolve under the influence of geometric and grey-level information, owing to the model of active contours. The performance of the method is evaluated according to the noise and is compared to the watershed algorithm. Then an application is finally presented for biomedical images of tumour tissue. (C) 1998 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：215 / 226
页数：12
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