Effectively Using Hyperspectral Imaging for Tissue Characterisation

Hyperspectral imaging is an advanced imaging technique used to capture and process information from across the electromagnetic spectrum. Unlike traditional imaging methods that capture data within specific bands of the spectrum (such as RGB in visible light), hyperspectral imaging collects and processes information across hundreds or even thousands of contiguous spectral bands. This technique provides a detailed spectral profile for each pixel in an image, offering a wealth of information beyond what traditional imaging methods can provide. Each pixel's spectral signature contains information about the object's chemical composition, material properties, and other specific characteristics that might not be visible to the human eye. <br /> <br /> Hyperspectral imaging in medicine offers unique capabilities for various applications, leveraging detailed spectral information to aid in diagnostics, tissue analysis, and disease detection. Some examples of how hyperspectral data is used in the medical field include Cancer Detection, Tissue Analysis and Histopathology, Endoscopy, and Minimally Invasive Surgery. Several proof-of-concept studies have shown that hyperspectral imaging is capable of distinguishing diseased from non-diseased cells and tissue. There is also mounting evidence that these technologies can help predict likely outcomes of the disease. However, state-of-the-art models designed to work with specific bands of the spectrum (such as RGB in visible light) fail to efficiently make use of the wealth of information provided by hyperspectral imaging.<br /> <br /> The topics for this project will focus on: <br /> * Computer vision and image understanding methods to extract higher-level <br /> semantic information from morphological images (medical/RGB). <br /> * Developing models that effectively use hyperspectral information in addition to <br /> morphological images. <br /> * Demonstrating the capabilities of models that effectively use hyperspectral <br /> imaging for tissue characterisation in clinical applications.<br /> <br /> A good knowledge of fundamental topics in computer vision and deep learning, along with strong coding skills in Python is expected. Experience with advanced deep learning topics, particularly multi-modal deep learning, attention models is preferred.<br />

<p>To apply for this project you will need to make a formal application for research degree study through the <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University website</a>. You will need to create a login ID with a username and PIN. </p> <p>•    For <strong>Application type</strong> please select <strong>Research Degrees – Research Postgraduate</strong>. <br /> •    The admission year for this project is <strong>2027/28</strong> Academic Year. <br /> •    You will need to select your <strong>Planned Course of Study</strong> from a drop-down menu. For this project, scroll down and select <strong>PHP Computer Science Full Time.</strong> <br /> •    The project start date for this project is <strong>1 October 2027</strong>, please use this as your <strong>Proposed Start Date of Research</strong>. <br /> •    Please state clearly in the<strong> Research Information Section</strong> that the research degree you wish to be considered for is <strong>Effectively Using Hyperspectral Imaging for Tissue Characterisation</strong> as well as <a href="https://eps.leeds.ac.uk/computing/staff/13320/dr-duygu-sarikaya">Dr Duygu Sarikaya</a> as your proposed supervisor</p> <p><strong>Please state clearly in the Finance section</strong>, <strong>the funding that you are applying for, if you are self-funding or externally sponsored</strong>.</p> <p>More information on how to apply is available on our website <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">here</a>. You will be required to provide a personal statement which outlines your interest in the project you are applying for, why you have chosen it and how your skills map onto the requirements of the project.</p> <p>We will assess applications continuously as we receive them. We welcome and strongly encourage any potential applicants to contact the supervisor(s) for an informal discussion, prior to applying, and recommend submitting your application early.</p> <p><strong>If you are applying with external sponsorship or you are funding your own study, please ensure you provide your supporting documents at the point you submit your application:</strong></p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date including the grading scheme</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul> <p>If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below).</p> <p><em>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.</em></p>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.5 overall with at least 6.5 in writing and 6.0 in reading, listening and speaking or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<p>This is a non funded PhD project. Applicants are expected to be self funded or to secure external funding.</p> <p>You can find out more about our Funding Opportunities on our <a href="https://phd.leeds.ac.uk/">Postgraduate Research Opportunities</a> website.</p> <p><strong>Important: </strong>Please note that all costs associated with your arrival at Leeds (<a href="https://www.leeds.ac.uk/international-visas-immigration/doc/applying-student-visa">visa, Immigration Health Surcharge</a>, flights etc) would have to be met by yourself, or you will need to find an alternative funding source.</p>

<p style="margin-bottom:11px">For further information about this project, please contact Dr Duygu Sarikaya by emailing <a href="mailto:D.Sarikaya@leeds.ac.uk">D.Sarikaya@leeds.ac.uk</a></p> <p>For further information about your application, including how to apply, please contact PGR Admissions by emailing <a href="mailto:phd@engineering.leeds.ac.uk">phd@engineering.leeds.ac.uk</a></p>