Show simple item record

AuthorKunhoth S.
AuthorAl-Maadeed, Somaya
Available date2022-05-19T10:23:12Z
Publication Date2017
Publication NameCommunications in Computer and Information Science
ResourceScopus
Identifierhttp://dx.doi.org/10.1007/978-3-319-60964-5_29
URIhttp://hdl.handle.net/10576/31138
AbstractAutomated tumor cell grading systems have an immense potential in improving the speed and accuracy of cancer diagnostic procedures. It can boost the confidence level of pathologists who perform the manual assessment of tumor cells. The application of image processing and machine learning techniques on the digitized biopsy slides enables the discrimination between various cell types. Deployment of multispectral imaging technique for biopsy slide digitization serves to provide spectral information along with the spatial information. Multispectral imaging allows to acquire several images of the sample in multiple wavelengths including the infrared ranges. This paper presents a multispectral image based colorectal tumor grading system. The algorithm validation is performed on our biopsy image database comprising 200 samples from 4 classes, viz. normal, hyperplastic polyp, tubular adenoma low grade as well as carcinoma cells. In addition to the visible bands, we have incorporated the spectral bands in near infrared ranges. Rotation invariant Local phase quantization (LPQ) feature extraction on our multispectral images have yielded a classification accuracy of 86.05% with an SVM classifier. Moreover, the experiments were carried out on another small multispectral image dataset which had 3 categories of cells.
SponsorThis publication was made possible using a grant from the Qatar National Research Fund through National Priority Research Program (NPRP) No. 6-249-1-053. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Qatar National Research Fund or Qatar University.
Languageen
PublisherSpringer Verlag
SubjectBiopsy
Cells
Cytology
Diagnosis
Grading
Image analysis
Image understanding
Imaging techniques
Infrared radiation
Learning systems
Medical imaging
Tumors
Classification accuracy
Colorectal tumors
Local phase quantizations
Machine learning techniques
Multispectral images
Multispectral imaging
Multispectral imaging techniques
Spectral information
Image processing
TitleMultispectral biopsy image based colorectal tumor grader
TypeConference Paper
Pagination330-341
Volume Number723
dc.accessType Abstract Only


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record