Shape and Boundary Similarity Features for Accurate HCC Image Recognition
Joint Authors
Duan, Xiaoyu
Li, Siqi
Jiang, Huiyan
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-07
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Nucleus morphology is of great importance in conventional cancer pathological diagnosis, which could provide information difference between normal and abnormal nuclei visually.
Therefore, this paper proposes two novel kinds of features for normal and hepatocellular carcinoma (HCC) nucleus recognition, including shape and boundary similarity.
First, each individual nucleus patch with the fixed size is obtained using center-proliferation segmentation (CPS) method.
Then, nucleus shape library is constructed based on manual selection by pathologists, which is utilized to measure nucleus shape similarity via Dice, Jaccard, precision, and recall coefficients.
Meanwhile, boundary similarity is evaluated through triangles composed of some boundary feature points for each nucleus.
Finally, the conventional random forest (RF) is used to train and test the classification model for HCC nucleus recognition.
Extensive cross-validation tests could facilitate the selection of the optimal feature set and the experiment comparison results demonstrate that our proposed morphological features are more beneficial for classification compared with other traditional characteristics.
American Psychological Association (APA)
Duan, Xiaoyu& Jiang, Huiyan& Li, Siqi. 2017. Shape and Boundary Similarity Features for Accurate HCC Image Recognition. BioMed Research International،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1136358
Modern Language Association (MLA)
Duan, Xiaoyu…[et al.]. Shape and Boundary Similarity Features for Accurate HCC Image Recognition. BioMed Research International No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1136358
American Medical Association (AMA)
Duan, Xiaoyu& Jiang, Huiyan& Li, Siqi. Shape and Boundary Similarity Features for Accurate HCC Image Recognition. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1136358
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136358