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Medical Vision-Language Models for Visual Question Answering


Key facts

Type of research degree
Application deadline
Ongoing deadline
Project start date
Tuesday 1 October 2024
Country eligibility
International (open to all nationalities, including the UK)
Competition funded
Source of funding
University of Leeds
Dr Duygu Sarikaya
Additional supervisors
Dr Nishant Ravikumar
School of Computing
<h2 class="heading hide-accessible">Summary</h2>

Vision language models (VLM) can process both visual information and natural language and learn associations between visual information and corresponding text descriptions. With their ability to extract semantics and insights from multi-modal data, they have shown impressive capabilities in tasks such as image captioning, visual question-answering, and text-to-image search. However, such models have seen limited adoption within real-world healthcare applications. Visual Question Answering (VQA) is a task that involves understanding and answering questions about images. It combines both computer vision, which interprets the content of images, and natural language processing, which deals with understanding and generating human language. The answers to these questions require an understanding of the image, the language, and domain-specific knowledge. <br /> <br /> Medical visual question answering models can assist clinicians in clinical decision-making and increase efficiency in the clinical workflow. They can be used to develop text-to-image search engines that allow users to query an image and its visual contents through natural language, making it possible to find medical images that fit specific criteria for research, discovery, or educational purposes. <br /> <br /> The main objectives of this project are: <br /> - Developing computer vision and image understanding methods to extract <br /> higher-level semantic information such as the detection of surgical tools, <br /> segmentation of an organ, and localization of tumours from medical image <br /> data. <br /> - Using state-of-the-art language models trained on medical corpora, finetuning <br /> these language models to a specific domain. <br /> -Training vision language models with paired datasets of medical images and <br /> their text descriptions, for visual question-answering and text-to-image search. <br /> - Demonstrating the capabilities of vision language models for clinical <br /> applications. <br /> <br /> The project will also explore open research problems in medical vision language models as they bring interesting challenges and opportunities in computer vision, natural language processing, and fundamental machine learning research. These open research problems may include medical image understanding, using language as weak supervision to train models, pre-training foundation models, training vision language models on medical corpora, learning to align image and text, etc.<br /> <br /> A good knowledge of fundamental topics in computer vision, machine learning and deep learning, along with strong coding skills in Python is expected. Experience with natural language processing and generative deep learning is not necessary but preferred.

<h2 class="heading">How to apply</h2>

<p style="margin-bottom:11px">Formal applications for research degree study should be made online through the&nbsp;<a href="">University&#39;s website</a>. Please state clearly in the Planned Course of Study section that you are applying for <strong><em>PHD Computing FT,</em></strong>&nbsp;in the research information section&nbsp;that the research degree you wish to be considered for is&nbsp;<em><strong>Medical Vision-Language Models for Visual Question Answering</strong></em>&nbsp;as well as <a href="">Dr Duygu Sarikaya</a>&nbsp;as your proposed supervisor and in the finance section, please state clearly&nbsp;<em><strong>the funding that you are applying for, if you are self-funding or externally sponsored</strong></em>.</p> <p>If English is not your first language, you must provide evidence that you meet the University&#39;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> <p>Applications will be considered after the closing date. &nbsp;Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. &nbsp;We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed.</p> <p>Please note that you must provide the following documents in support of your application by the closing date of 3 April 2024 for Leeds Opportunity Research Scholarship or&nbsp;8 April 2024 for Leeds Doctoral Scholarship:</p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul>

<h2 class="heading heading--sm">Entry requirements</h2>

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.

<h2 class="heading heading--sm">English language requirements</h2>

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 at least 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.

<h2 class="heading">Funding on offer</h2>

<p><strong>Self-Funded or externally sponsored students are welcome to apply.</strong></p> <p><strong>UK</strong>&nbsp;&ndash;&nbsp;The&nbsp;<a href="">Leeds Doctoral Scholarships</a>&nbsp;and&nbsp;<a href="">Leeds Opportunity Research Scholarship</a>&nbsp;(will reopen from October 2024 for 2025/26 academic entry)&nbsp;are available to UK applicants.&nbsp;<a href="">Alumni Bursary</a>&nbsp;is available to graduates of the University of Leeds.</p> <p><strong>Non-UK</strong>&nbsp;&ndash; The&nbsp;<a href="">China Scholarship Council - University of Leeds Scholarship</a>&nbsp;is available to nationals of China (will reopen from October 2024 for 2025/26 academic entry). The&nbsp;<a href="">Leeds Marshall Scholarship</a>&nbsp;is available to support US citizens.&nbsp;<a href="">Alumni Bursary</a>&nbsp;is available to graduates of the University of Leeds.</p> <p><strong>Important:</strong>&nbsp; Any costs associated with your arrival at the University of Leeds to start your PhD including flights, immigration health surcharge/medical insurance and Visa costs are not covered under this studentship.</p> <p>Please refer to the&nbsp;<a href="">UKCISA</a>&nbsp;website for information regarding Fee Status for Non-UK Nationals.</p>

<h2 class="heading">Contact details</h2>

<p style="margin-bottom:11px">For further information about this project, please contact Dr Duygu Sarikaya by email to&nbsp;<a href=""></a></p> <p>For further information about your application, please contact Doctoral College Admissions by email to <a href=""></a></p>