DocumentCode :
702757
Title :
Review paper on histopathological image analysis approach for automatic detection of glandular structures in human tissue
Author :
Kawalkar, Prachi ; Talmale, Girish
Author_Institution :
Dept. of Comput. Sci. & Eng., G.H. Raisoni Coll. of Eng., Nagpur, India
fYear :
2015
fDate :
8-10 Jan. 2015
Firstpage :
1
Lastpage :
5
Abstract :
In the last few decades, a dynamic growth within the range of analysis works conducted within the space of organ structure designation. This paper gives short reviews computer assisted histopathology image analysis for gland detection, segmentation and classification. The term Histopathology refers to the study of changes in biopsy sample taken by a pathologist under microscope. Main task of pathologist is to analyzing, locating and classifying most of the diseases, similarly appear at the tissue structure, distribution of cells in tissue, regularities of cell shapes and determine benign and syndrome in image. It is very important because the gland in human tissues is the area where cancer can be experiential. But this process is too time consuming and lead to intra and inter observer variability. To remove this drawback automatic detection of images is needed for quantitative diagnosis of Tissue. In this paper we have consolidated such recent techniques and its unique features. The survey done provides different approaches for detecting glands and the parameters considered for same. Discussion is also made on various Databases used for detection of glandular structure.
Keywords :
biological organs; biological tissues; cancer; image classification; image segmentation; medical image processing; object detection; automatic glandular structure detection; benign; cancer; cell distribution; cell shapes; computer assisted histopathology image analysis approach; gland classification; gland detection; gland segmentation; human tissue structure; interobserver variability; intraobserver variability; organ structure designation; syndrome; Cancer; Feature extraction; Glands; Image analysis; Image color analysis; Image segmentation; Cancer; Gleason Grading System; Graph Theory; Medical Diagnosis; Texture Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing (ICPC), 2015 International Conference on
Conference_Location :
Pune
Type :
conf
DOI :
10.1109/PERVASIVE.2015.7087153
Filename :
7087153
Link To Document :
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