Recently, Dr. Xiayu Xu from BEBC has published her first author paper in Biomedical Optics Express entitled " Simultaneous
arteriole and venule segmentation with domain-specific loss function on a new
public database ".
Abstract graph of this study
In this paper, they studied the segmentation and
classification of retinal arterioles and venules which play an important role
in the diagnosis of various eye diseases and systemic diseases. The major
challenges include complicated vessel structure, inhomogeneous illumination,
and large background variation across subjects. In this study, they employ a
fully convolutional network to simultaneously segment arterioles and venules
directly from the retinal image, rather than using a vessel
segmentation-arteriovenous classification strategy as reported in most
literature. To simultaneously segment retinal arterioles and venules, we
configured the fully convolutional network to allow true color image as input
and multiple labels as output. A domain-specific loss function was designed to
improve the overall performance. The proposed method was assessed extensively
on public data sets and compared with the stateof-the-art methods in
literature. The sensitivity and specificity of overall vessel segmentation on
DRIVE is 0.944 and 0.955 with a misclassification rate of 10.3% and 9.6% for
arteriole and venule, respectively. The proposed method outperformed the
state-of-the-art methods and avoided possible error-propagation as in the
segmentation-classification strategy. The proposed method was further validated
on a new database consisting of retinal images of different qualities and
diseases. The proposed method holds great potential for the diagnostics and
screening of various eye diseases and systemic diseases.
The co-authors of the paper include Rendong
Wang, PeiLin Lv, Bin Gao, Chan Li, ZhiQiang Tian, Tao Tan and Feng Xu.
