Header Information

NPRP 6 - 249 - 1 - 053
NPRP 06
Qatar University
Award Closed
01 Apr 2014
Dr. Somaya Al-Maadeed
3 Year(s)
17 Jan 2018
New
Automated Classification and Diagnosis of Tissue Patterns in Colorectal Tumours Using Non-Visible Multispectral Imagery

Project Summary
Quantitative cell imagery in cancer pathology has progressed greatly in the last 30 years where the diagnosis is still critically reliant upon the analysis of biopsy samples which are usually analyzed by a trained pathologist who, by analyzing the biopsies under microscope, assesses the normality or malignancy of the samples submitted. The diagnosis is crucial for determining a course of treatment. Recently, a pioneering work by the LPI has concentrated on using multispectral imagery using up to 64 spectral bands. There is increasing evidence that the much wider area beyond the visible spectrum is an interesting medium to study from a pathological point of view. In particular, the mid-infrared (MIR) bands contain richer information content than the visible bands. This proposal will investigate the use of multispectral imagery in both visible and MIR bands. We intend to combine information from the multispectral bands of both the visible and MIR bands with view to understanding the biochemistry of colorectal cancer and hence develop a robust and accurate multispectral computer aided system for automatic colorectal cancer detection, classification and diagnosis using visible and non-visible spectra. This will be used by the pathologists to assist them in the early detection of colorectal cancer. In addition, the methods, software and hardware tools which will be produced should be very applicable to classification of other cancer types such as lung, breast, cervix etc.
-Medical Health-Care System: If successful, the proposed research should enable the leading Qatar research and industrial companies to develop internationally competitive products for all other types of cancer identification and classification. The main outcome of this project would be a computer aided diagnosis system for colon cancer detection and classification using multispectral imaging.There is a sezeable number of public and private hospitals in the State of Qatar. On completion of this project, the computer aided diagnosis system would help improve the health care system in these hospitals due to early detection of early stage colon cancer thus allowing a successful treatment. -Advancing Research Base in Qatar: This research project will also have a high impact on the advancement of academic research in Qatar. Of particular interest to the broader research and academic community would be the algorithmic developments for quantitative pathology, especially of novel multispectral texture analysis using various pattern recognition and multispectral image processing , such as the MuLBP, MULPQ that are self adaptive and hence provide a high degree of optimization and also approaches using soft computing based fusion methods. These algorithms are likely to be relevant to other application areas, such as remote sensing, texture based image analysis, etc.
Multispectral imaging; Image processing; Feature extraction; Cancer detection; Cancer imaging
Applied research
1. Natural Sciences
1.2 Computer and Information Sciences
Information Science and Bioinformatics
Yes
No
2. Engineering and Technology
2.06 Medical Engineering
Medical Laboratory Technology
No
Yes

Institution
Qatar University
Qatar
Submitting Institution
Al Ahli Hospital
Qatar
Collaborative Institution
École Polytechnique de Montréal
Canada
Collaborative Institution
Northumbria University
United Kingdom
Collaborative Institution

Personnel
Lead PI
Dr. Somaya Al-Maadeed
Qatar University
Co-Lead PI
Dr. Somaya Al-Maadeed
Qatar University
PI
Prof. Mohamad Sawan
École Polytechnique de Montréal
PI
Prof. Ahmed Bouridane
Northumbria University
PI
Dr. Fouad Khelifi
Northumbria University
Co-PI
Dr. rafif mahmood alsaady
Al Ahli Hospital
Co-PI
Dr. Muhammad Tahir
Northumbria University

Outputs/Outcomes
Journal Paper
Medical and Computing Insights into Colorectal Tumors
Suchithra Kunhoth, Somaya Al Maadeed, Ahmed Bouridane, Rafif Al Saady, and Ahmed Bouridane
ISSN: 22503137
Conference Paper
Texture Analysis for Colorectal Tumour Biopsies using Multispectral Imagery
Peyret, Remy; Bouridane, Ahmed; Al-Maadeed, Somaya Ali; Kunhoth, Suchithra; Khelifi, Fouad
DOI:10.1109/EMBC.2015.7320057
Conference Paper
Building a multispectral image dataset for colorectal tumor biopsy
Suchithra Kunhoth ; Somaya Al Maadeed
DOI:10.1109/IWCMC.2017.7986548
Conference Paper
Multispectral Biopsy Image Based Colorectal Tumor Grader
Suchithra Kunhoth, Somaya Al Maadeed
DOI:https://doi.org/
Conference Paper
Multispectral imaging and machine learning for automated cancer diagnosis
Somaya Al Maadeed ; Suchithra Kunhoth ; Ahmed Bouridane ; Remy Peyret
DOI:10.1109/IWCMC.2017.7986547
Conference Paper
Automatic diagnosis of prostate cancer using multispectral based linear binary pattern bagged codebooks
Rémy Peyret ; Fouad Khelifi ; Ahmed Bouridane ; Somaya Al-Maadeed
DOI:10.1109/BIOSMART.2017.8095322
Journal Paper
Automatic classification of colorectal and prostatic histologic tumor images using multiscale multispectral local binary pattern texture features and stacked generalization
émy Peyret, Ahmed Bouridane, Fouad Khelifi, Muhammad Atif Tahir, Somaya Al-Maadeed
ISSN:09252312
Journal Paper
Palmprint Identification Using an Ensemble of Sparse Representations
Somaya Al Maadeed1 · Xudong Jiang2 · Imad Rida1 · Ahmed Bouridane3
ISSN: 13807501
Journal Paper
Palmprint Identification Using an Ensemble of Sparse Representations
IMAD RIDA1, SOMAYA AL-MAADEED1, ARIF MAHMOOD 1, AHMED BOURIDANE2 and SAMBIT BAKSHI3.
ISSN:21693536
Journal Paper
Palmprint identification using sparse and dense hybrid representation
Somaya Al Maadeed1 · Xudong Jiang2 · Imad Rida1 · Ahmed Bouridane3
ISSN:13807501