This is your project contract form. The deadline is 2/12/2022 12:00 noon. Remember to tick “Send me an email receipt of my responses” at the end of this page to receive a confirmation email. Please note that you need to forward the “confirmation email” to your supervisor in order to validate this submission.
1.Student Name: Georgia Savva
2.P-number: P2565675
3.Programme: Computer Science
4.Email address: P2565675@my33665.dmu.ac.uk
5.Project Title: Deep learning-based detection of blood clots in the lung.
6.Project Proposer: This project aims to develop a machine learning model to perform quick and accurate blood clot detection in lungs.
7.Supervisor: Stephen Adusei
8.Introduction: Lung blood clot detection is critical for clinicians, as early diagnosis and treatment can prevent potentially fatal outcomes. However, the task is difficult, as pulmonary embolism (a blood clot in the lungs) can be challenging to diagnose, particularly in its early stages. The current standard of care for detecting blood clots in the lung is a CT scan, which is expensive and exposes the patient to radiation.
Recent advances in deep learning have shown promise for the automated detection of a wide range of medical conditions. In this proposal, I seek to apply deep learning to detect lung blood clots.
9.Project Background: The main components of blood include plasma, red blood cells (RBC), white blood cells (WBC) and platelets. Plasma is a clear, colourless fluid that contains water and other substances and comprises about 55 per cent of blood volume. It contains many vital life functions such as the transport of oxygen in the body, blood clotting capability and hormonal regulation and is responsible for blood clotting.
Blood clots are one of the most important reasons for stroke and coronary heart attack. Blood can become trapped in sticky blood vessels and block blood flow. This results in a life-threatening situation if blood clots block your brain or heart, causing a stroke or heart attack. Blood clotting can start at any age but usually happens in your 20s and 30s. Signs and symptoms include headache, sudden pain in the chest, arm or leg, numbness or tingling in one or more body parts, rapid heartbeat/heart palpitations and shortness of breath.
There are a variety of diagnostic techniques that physicians can use when a blood clot is suspected. Specific tests use imaging tools such as duplex ultrasound, magnetic resonance imaging (MRI), venography, computed tomography scans, magnetic resonance angiography, D-Dimer test, arteriography/angiography, and impedance plethysmography.
These techniques differ in their methods of determining the presence of blood clots and are specifically designed to detect various medical conditions. They are expensive, inaccurate and prone to delayed diagnosis, so not all laboratories have them available.
Many types of research were studied to detect blood clots in early stages using neural network models [1], [2], [3], genetic algorithms [4] and Artificial intelligence [5].
In this paper, we will use deep learning methods to predict lung blood clots. Deep learning is a fascinating area of computer science with many applications in the real world. It has already shown power in many application fields and has excellent potential to improve the overall performance of machine learning systems.
Deep learning detection of blood clots in the lungs works by training a deep neural network to identify blood clots in the lungs. The network is trained with a set of images. Once trained, the network can quickly identify blood clots in new images based on their shape and location.
10.Aims: Blood clots in the lung can have devastating consequences. There is no easy or reliable way to detect them, so the best way to avoid problems is to prevent them. This project aims to develop a machine-learning model to perform quick and accurate blood clot detection in the lungs.
11.Objectives (max. 200 words):
General Objective:
The general objective of this project is to apply deep learning in order to detect blood clots in lungs. This can save lives of people who have pulmonary embolism, a potentially fatal condition that involves clots in the arteries of the lung.
Specific Objective:
The following specific objectives will be accomplished to achieve the general objective of the study.
- To conduct a comprehensive systematic literature review to identify methods, algorithms and approaches used in this study.
- Label the data by experts.
- To prepare training and test dataset.
- To identify suitable deep learning algorithms.
- To develop an optimal model to detect a blood clot in the lungs.
- To test and evaluate the performance of the proposed model.
12.Deliverables (max. 100 words):
Project First Declaration:
- Project Contract
- Ethical Screening
First Deliverable:
- Literature review (2000 words)
- Functional requirements
- Indicative test plan
- System design documentation
- Implementation report (300 words)
Final Deliverable:
- Main Report
- Viva
- The System
- Project Supervisor Meetings
13.Resources and Constraints (max. 100 words):
Microsoft Teams
Python programming language will be used
Project Gantt chart
SharePoint
OneDrive
VMWare horizon
Microsoft Office Applications
14.Sources of Information (max. 100 words):
Google Scholar
DMU Library
15. Risk Analysis (max. 100 words): Performing a risk analysis on blood clot detection with deep learning is a complex yet essential task. I will use the following steps to analyse and mitigate risks to ensure successful blood clot detection.
- Establish a Risk Framework
- Analyse Data
- Implement Deep Learning Model
- Monitor Performance
16.Schedule of Activities (max. 300 words): This project is an incredibly important one that will require a lot of time and effort. Luckily, I have created a simple schedule to help us stay on track and complete the project on time.
17. Please indicate which of these possible attributes is addressed by your undertaking of this project. You should select at least two items.
| Addressed by Project? | |
| 1- Ability to work collaboratively: teams from a range of backgrounds and countries | |
| 2- Excellent communication skills with a sensitivity to speaking with and listening to non-native English speakers | |
| 3- An ability to embrace multiple perspectives and challenge thinking in a range of cultural context | √ |
| 4- A capacity to develop new skills and behaviours according to role requirements | √ |
| 5- An ability to negotiate and influence clients across the globe from different cultures | |
| 6- An ability to form professional, global networks | |
| 7- An openness to/respect of a range of perspectives from around the world | |
| 8- Multi-cultural learning agility (i.e., able to learn in any culture or environment) |
18.Brief description of how the ticked attributes have been addressed :
The ability to develop new skills and behaviours is essential in any workplace. This project will help me not only develop the skills and behaviours required for my current role but also to be able to identify and develop new skills and behaviours as my role and responsibilities change. It will also help me to develop an understanding of the different ways in which people from different cultural backgrounds think and behave.
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