Computer aided system for dendritic cells detection and counting

lmmunotherapy is an entirely advanced class of cancer treatment which has been highly active and exciting field in clinical therapeutics. In numerous procedures, cancer immunotherapy demands a laborious practice to recognise and count Dendritic Cells (DCs) in the harnessing of immune system. Convent...

Full description

Saved in:

Bibliographic Details
Main Author:	Muhd Suberi, Anis Azwani
Format:	Thesis
Language:	English English English
Published:	2017
Subjects:	QR Microbiology
Online Access:	http://eprints.uthm.edu.my/7830/2/24p%20ANIS%20AZWANI%20MUHD%20SUBERI.pdf http://eprints.uthm.edu.my/7830/1/ANIS%20AZWANI%20MUHD%20SUBERI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7830/3/ANIS%20AZWANI%20MUHD%20SUBERI%20WATERMARK.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uthm-ep.7830
record_format	uketd_dc
spelling	my-uthm-ep.78302022-10-12T02:23:45Z Computer aided system for dendritic cells detection and counting 2017-05 Muhd Suberi, Anis Azwani QR Microbiology lmmunotherapy is an entirely advanced class of cancer treatment which has been highly active and exciting field in clinical therapeutics. In numerous procedures, cancer immunotherapy demands a laborious practice to recognise and count Dendritic Cells (DCs) in the harnessing of immune system. Conventionally, the laser-based technology that provides a rapid analysis such as Flow Cytometry can affect the DCs viability as the staining procedure is involved. Another highly promising method which is Phase Contrast Microscopy (PCM) involves experienced pathologists to visually examine the respective microscopy images. In fact, PCM confronts complex issues regarding imaging artifacts which can deteriorate the recognition process. As DCs counting are crucial in most cancer treatment procedures, this research proposes a pioneering system called CasDC (Computer Aided System for Dendritic Cells identification) which implements an image processing algorithm to recognise and count DCs with a label-free method. Initially, the images undergo Grayscale Normalization, H-GLAT, and Halo Removal to remove the imaging artifacts. In segmentation, morphological operators and Canny edge detector are implemented to extract the cell contours. Following that, information from the contours are characterized through the use of One-Dimensional (ID) Fourier Descriptors (FDs) and classified using Template Matching (TM). The aim of developing this system is to establish a reliable and time saving-tool as a second reader in the clinical practice. The proposed system has an enormous potential towards helping Cancer Research Institute in improving the diagnosis of cancer. Through the experiments conducted on dataset provided by the Cancer Research Institute, performance measures of 83.8%, 94.2%, 99 .5% and 88. 7% have been recorded for precision, recall, accuracy and FI-score respectively . 2017-05 Thesis http://eprints.uthm.edu.my/7830/ http://eprints.uthm.edu.my/7830/2/24p%20ANIS%20AZWANI%20MUHD%20SUBERI.pdf text en public http://eprints.uthm.edu.my/7830/1/ANIS%20AZWANI%20MUHD%20SUBERI%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/7830/3/ANIS%20AZWANI%20MUHD%20SUBERI%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QR Microbiology
spellingShingle	QR Microbiology Muhd Suberi, Anis Azwani Computer aided system for dendritic cells detection and counting
description	lmmunotherapy is an entirely advanced class of cancer treatment which has been highly active and exciting field in clinical therapeutics. In numerous procedures, cancer immunotherapy demands a laborious practice to recognise and count Dendritic Cells (DCs) in the harnessing of immune system. Conventionally, the laser-based technology that provides a rapid analysis such as Flow Cytometry can affect the DCs viability as the staining procedure is involved. Another highly promising method which is Phase Contrast Microscopy (PCM) involves experienced pathologists to visually examine the respective microscopy images. In fact, PCM confronts complex issues regarding imaging artifacts which can deteriorate the recognition process. As DCs counting are crucial in most cancer treatment procedures, this research proposes a pioneering system called CasDC (Computer Aided System for Dendritic Cells identification) which implements an image processing algorithm to recognise and count DCs with a label-free method. Initially, the images undergo Grayscale Normalization, H-GLAT, and Halo Removal to remove the imaging artifacts. In segmentation, morphological operators and Canny edge detector are implemented to extract the cell contours. Following that, information from the contours are characterized through the use of One-Dimensional (ID) Fourier Descriptors (FDs) and classified using Template Matching (TM). The aim of developing this system is to establish a reliable and time saving-tool as a second reader in the clinical practice. The proposed system has an enormous potential towards helping Cancer Research Institute in improving the diagnosis of cancer. Through the experiments conducted on dataset provided by the Cancer Research Institute, performance measures of 83.8%, 94.2%, 99 .5% and 88. 7% have been recorded for precision, recall, accuracy and FI-score respectively .
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Muhd Suberi, Anis Azwani
author_facet	Muhd Suberi, Anis Azwani
author_sort	Muhd Suberi, Anis Azwani
title	Computer aided system for dendritic cells detection and counting
title_short	Computer aided system for dendritic cells detection and counting
title_full	Computer aided system for dendritic cells detection and counting
title_fullStr	Computer aided system for dendritic cells detection and counting
title_full_unstemmed	Computer aided system for dendritic cells detection and counting
title_sort	computer aided system for dendritic cells detection and counting
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2017
url	http://eprints.uthm.edu.my/7830/2/24p%20ANIS%20AZWANI%20MUHD%20SUBERI.pdf http://eprints.uthm.edu.my/7830/1/ANIS%20AZWANI%20MUHD%20SUBERI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7830/3/ANIS%20AZWANI%20MUHD%20SUBERI%20WATERMARK.pdf
_version_	1747831199308447744

Computer aided system for dendritic cells detection and counting

Similar Items