Diagnosis and Treatment of Small Bowel Disorders

Over the last few decades, remarkable progress has been made in understanding the aetiology and pathophysiology of diseases and many new theories emphasize the importance of the small bowel ‘ecosystem’ in the pathogenesis of acute and chronic illness. Emerging factors such as microbiome, stem cells, innate intestinal immunity and the enteric nervous system along with mucosal and endothelial barriers have key role in the development of gastrointestinal and extra-intestinal diseases. Therefore, the small intestine is considered key player in metabolic disease development, including diabetes mellitus, and other diet-related disorders such as celiac and non-celiac enteropathies. Another major field is drug metabolism and its interaction with microbiota. Moreover, the emergence of gut-brain, gut-liver and gut-blood barriers points toward the important role of small intestine in the pathogenesis of common disorders, such as liver disease, hypertension and neurodegenerative disease. However, the small bowel remains an organ that is difficult to fully access and assess and accurate diagnosis often poses a clinical challenge. Eventually, the therapeutic potential remains untapped. Therefore, it is due time to direct our interest towards the small intestine and unravel the interplay between small-bowel and other gastrointestinal (GI) and non-GI related maladies

Building a multispectral image dataset for colorectal tumor biopsy

Automated grading of tumor cells proves to be a great way of enhancing the rapidity and accuracy of cancer diagnostic procedures. The application of image processing and machine learning techniques on the digitized biopsy slides enables the discrimination between various cell types. Apart from using the normal RGB/grayscale imaging, multispectral images tend to provide a wide range of information that can support the classification tasks. Besides using the visible range, wavelength bands in infrared ranges can be utilized in multispectral imaging. This paper presents our multispectral image acquisition system to develop a database for the colorectal biopsy slides. The dataset comprise images in both visible and near infrared spectrum for the 4 major categories of colon cells. A preprocessing algorithm with automatic estimation of parameters for adaptive histogram equalization is also presented. With the acquired database, our preliminary experiment involving a basic feature extraction and classification algorithm yielded satisfactory results.This 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.Scopu