Diabetic Retinopathy Detection Using Matlab Assignment 2022
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Running Head: PROJECT MANAGEMENT
Diabetic Retinopathy Detection using MATLAB
Name of the Student
Name of the University
Diabetic Retinopathy Detection using MATLAB
Name of the Student
Name of the University
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1PROJECT MANAGEMENT
Project Budget
The overall project budget includes hardware and software resources required for the
simulation works that have been proposed for the project, wages of the project team members (if
any) and other relevant costs. While the hardware and software costs are fixed, it can be
determined based on the market prices. On the other hand, payments for the internal and external
team members of the project, the total cost is to be determined by specifying their working hours
and their basic wages per hour. This process can be done by allocating each of the human
resources in the project work breakdown structure that includes the schedule of the project.
However, in this case, there are no external human resources required and hence, the costs only
include material resources. The budget breakdown is thus developed and shown as follows.
Resource Name Std. Rate
Hardware Equipments $1,500.00
Software $750.00
Software Toolkits $250.00
Other Costs $500.00
Total $3000
Project Schedule
The project schedule is shown in the following table.
WBS Task Name Duration Start Finish Predecessors
0 Diabetic Retinopathy Detection using MATLAB 118 days Tue 05-03-
19
Thu 15-08-
19
Project Budget
The overall project budget includes hardware and software resources required for the
simulation works that have been proposed for the project, wages of the project team members (if
any) and other relevant costs. While the hardware and software costs are fixed, it can be
determined based on the market prices. On the other hand, payments for the internal and external
team members of the project, the total cost is to be determined by specifying their working hours
and their basic wages per hour. This process can be done by allocating each of the human
resources in the project work breakdown structure that includes the schedule of the project.
However, in this case, there are no external human resources required and hence, the costs only
include material resources. The budget breakdown is thus developed and shown as follows.
Resource Name Std. Rate
Hardware Equipments $1,500.00
Software $750.00
Software Toolkits $250.00
Other Costs $500.00
Total $3000
Project Schedule
The project schedule is shown in the following table.
WBS Task Name Duration Start Finish Predecessors
0 Diabetic Retinopathy Detection using MATLAB 118 days Tue 05-03-
19
Thu 15-08-
19
2PROJECT MANAGEMENT
1 Initialization 8 days Tue 05-03-
19
Thu 14-03-
19
1.1 Searching for Project Topic 2 days Tue 05-03-
19
Wed 06-03-
19
1.2 Submitting the project topic 1 day Thu 07-03-
19
Thu 07-03-
19 2
1.3 Waiting for the Project approval 4 days Fri 08-03-
19
Wed 13-03-
19 3
1.4 Submitting Project Proposal 1 day Thu 14-03-
19
Thu 14-03-
19 4
2 Planning 22 days Fri 15-03-
19
Mon 15-04-
19
2.1 Consulting with assigned Supervisor for upcoming plans 2 days Fri 15-03-
19
Mon 18-03-
19 5
2.2 Searching for High performance Laptop & Camera 4 days Tue 19-03-
19 Fri 22-03-19 7
2.3 Research of and studying the codes 10 days Mon 25-03-
19 Fri 05-04-19 8
2.4 Collecting retinal images 6 days Mon 08-04-
19
Mon 15-04-
19 9
3 Execution 47 days Tue 16-04-
19
Wed 19-06-
19
3.1 Visit medical clinics 7 days Tue 16-04-
19
Wed 24-04-
19 10
3.2 Work on MATLAB 25 days Thu 25-04-
19
Wed 29-05-
19 12
3.3 Work on the project report 15 days Thu 30-05-
19
Wed 19-06-
19 13
4 Monitoring and Controlling 20 days Thu 20-06-
19
Wed 17-07-
19
4.1 Testing MATLAB Codes flow 12 days Thu 20-06-
19 Fri 05-07-19 14
4.2 Testing the stability 5 days Mon 08-07-
19 Fri 12-07-19 16
4.3 Prototyping model 3 days Mon 15-07-
19
Wed 17-07-
19 17
5 Project Closure 21 days Thu 18-07-
19
Thu 15-08-
19
5.1 Testing Flow of MATLAB Codes 9 days Thu 18-07- Tue 30-07- 18
1 Initialization 8 days Tue 05-03-
19
Thu 14-03-
19
1.1 Searching for Project Topic 2 days Tue 05-03-
19
Wed 06-03-
19
1.2 Submitting the project topic 1 day Thu 07-03-
19
Thu 07-03-
19 2
1.3 Waiting for the Project approval 4 days Fri 08-03-
19
Wed 13-03-
19 3
1.4 Submitting Project Proposal 1 day Thu 14-03-
19
Thu 14-03-
19 4
2 Planning 22 days Fri 15-03-
19
Mon 15-04-
19
2.1 Consulting with assigned Supervisor for upcoming plans 2 days Fri 15-03-
19
Mon 18-03-
19 5
2.2 Searching for High performance Laptop & Camera 4 days Tue 19-03-
19 Fri 22-03-19 7
2.3 Research of and studying the codes 10 days Mon 25-03-
19 Fri 05-04-19 8
2.4 Collecting retinal images 6 days Mon 08-04-
19
Mon 15-04-
19 9
3 Execution 47 days Tue 16-04-
19
Wed 19-06-
19
3.1 Visit medical clinics 7 days Tue 16-04-
19
Wed 24-04-
19 10
3.2 Work on MATLAB 25 days Thu 25-04-
19
Wed 29-05-
19 12
3.3 Work on the project report 15 days Thu 30-05-
19
Wed 19-06-
19 13
4 Monitoring and Controlling 20 days Thu 20-06-
19
Wed 17-07-
19
4.1 Testing MATLAB Codes flow 12 days Thu 20-06-
19 Fri 05-07-19 14
4.2 Testing the stability 5 days Mon 08-07-
19 Fri 12-07-19 16
4.3 Prototyping model 3 days Mon 15-07-
19
Wed 17-07-
19 17
5 Project Closure 21 days Thu 18-07-
19
Thu 15-08-
19
5.1 Testing Flow of MATLAB Codes 9 days Thu 18-07- Tue 30-07- 18
3PROJECT MANAGEMENT
19 19
5.2 Finalizing Project report 5 days Wed 31-07-
19
Tue 06-08-
19 20
5.3 Reviewing the project work with supervisor 2 days Wed 07-08-
19
Thu 08-08-
19 21
5.4 Project pre-demonstration 2 days Fri 09-08-
19
Mon 12-08-
19 22
5.5 Closing the project 2 days Tue 13-08-
19
Wed 14-08-
19 23
5.6 Submitting the final report 1 day Thu 15-08-
19
Thu 15-08-
19 24
Risk Management
In this project, there are several risks associated that are showing along with the
mitigation plan in the following table.
Risk Description Chance of Occurrence Impact on Project Mitigation Plan
Faulty hardware can
result in delaying or
blocking the project
Medium Medium During purchase of
hardware, the quality
should be verified and
tested.
Software purchased may
be of pirated version
High High Software should only be
purchased and
downloaded from
verified vendors at
proper price instead of
free pirated versions
19 19
5.2 Finalizing Project report 5 days Wed 31-07-
19
Tue 06-08-
19 20
5.3 Reviewing the project work with supervisor 2 days Wed 07-08-
19
Thu 08-08-
19 21
5.4 Project pre-demonstration 2 days Fri 09-08-
19
Mon 12-08-
19 22
5.5 Closing the project 2 days Tue 13-08-
19
Wed 14-08-
19 23
5.6 Submitting the final report 1 day Thu 15-08-
19
Thu 15-08-
19 24
Risk Management
In this project, there are several risks associated that are showing along with the
mitigation plan in the following table.
Risk Description Chance of Occurrence Impact on Project Mitigation Plan
Faulty hardware can
result in delaying or
blocking the project
Medium Medium During purchase of
hardware, the quality
should be verified and
tested.
Software purchased may
be of pirated version
High High Software should only be
purchased and
downloaded from
verified vendors at
proper price instead of
free pirated versions
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
4PROJECT MANAGEMENT
Legal, Social, Ethical and Sustainability Aspects
The term “Diabetes” refers to a chronic disease that involves metabolic disorder of a
person that results in high blood sugar level in that particular person. High blood sugar level for a
long amount of time is harmful for the body as it starts harming various organs including liver,
stomach, eyes and others (Kim et al. 2016). The medical condition that occurs when the eyes are
affected by diabetes is known as diabetic retinopathy and it results in partial or complete
blindness on one or both eyes. The blindness occurs as the high blood sugar affects the retina of
the eyes. The purpose of this project is to develop an automated and computerised system using
MATLAB that will be able to help the detection of diabetic retinopathy.
There are various technological advancements that have provided various machines and
automated systems that have been utilised in the hospitals and clinics for treatment and diagnosis
purposes. However, currently there are no devices for detecting diabetic retinopathy at early
stages – it can only be detected once it has already caused significant damages to the eyes of the
affected. Any new type of technology similar to the one discussed in this report is entirely new
and untested on actual patients (Tan et al. 2017). Hence, there are certain legal, social, ethical
and sustainability aspects associated with this technology. Before launching this system for use
in clinics, these aspects must be properly considered and the issues must be addressed. First,
awareness needs to be raised such that the patients are aware about the full functioning of the
system. Second, ethical and legal issues must be addressed before allowing the system to be used
commercially. Finally, the overall system including the hardware and software used must be
sustainable and cost effective in order to use it commercially in the hospitals and clinics for the
diagnosis and treatment of the patients.
Legal, Social, Ethical and Sustainability Aspects
The term “Diabetes” refers to a chronic disease that involves metabolic disorder of a
person that results in high blood sugar level in that particular person. High blood sugar level for a
long amount of time is harmful for the body as it starts harming various organs including liver,
stomach, eyes and others (Kim et al. 2016). The medical condition that occurs when the eyes are
affected by diabetes is known as diabetic retinopathy and it results in partial or complete
blindness on one or both eyes. The blindness occurs as the high blood sugar affects the retina of
the eyes. The purpose of this project is to develop an automated and computerised system using
MATLAB that will be able to help the detection of diabetic retinopathy.
There are various technological advancements that have provided various machines and
automated systems that have been utilised in the hospitals and clinics for treatment and diagnosis
purposes. However, currently there are no devices for detecting diabetic retinopathy at early
stages – it can only be detected once it has already caused significant damages to the eyes of the
affected. Any new type of technology similar to the one discussed in this report is entirely new
and untested on actual patients (Tan et al. 2017). Hence, there are certain legal, social, ethical
and sustainability aspects associated with this technology. Before launching this system for use
in clinics, these aspects must be properly considered and the issues must be addressed. First,
awareness needs to be raised such that the patients are aware about the full functioning of the
system. Second, ethical and legal issues must be addressed before allowing the system to be used
commercially. Finally, the overall system including the hardware and software used must be
sustainable and cost effective in order to use it commercially in the hospitals and clinics for the
diagnosis and treatment of the patients.
5PROJECT MANAGEMENT
For this diabetic retinopathy detection system, the legal, social, ethical and sustainability
aspects associated with diabetic retinopathy detection that are discussed as follows.
Social Aspects – The first main social aspect is that the patients may not agree to be
tested with a new type of technology that involves computer simulation. This is mainly because
this is a new and untested technology that have not been extensively used in any clinics. As a
result, the patients are not aware whether there are any risks with the process (Canche, Dalmau
and García 2017). The patients will never accept any clinical procedure that does not ensure that
their organs will not be further damaged. Hence, before releasing this technology for clinical use,
a lot of detailed testing and raising awareness are necessary so as to convince the patients that the
process is very safe for the clinical treatment and diagnosis. The overall testing process should
include the functionality of the system, the impact of its use on the body and organs of the
patients, any negative aspects and others. There are many medical devices that can cause
significant side effects on the patients’ bodies and hence, these types of devices are only used in
urgent situations (Majumdar et al. 2015). Moreover, the patients often do not allow the use of
devices that have side effects or the possible side effects are not known to the doctors. Once the
testing of the system is complete, it is important for the clinics and hospitals to raise awareness
so that the patients understand the working of the devices and whether they will have any
negative impact on their bodies rather than benefitting them.
Ethical Aspects – There are also ethical aspects associated with this particular technology
and it is almost similar to the social aspect. Using this untested technology with the patients’
proper knowledge or permission can raise several ethical concerns regarding the treatment
process (Krawitz et al. 2017). Again, since this is a computerised process, the personal and
clinical information of the patients need to be entered into the system and stored in the cloud
For this diabetic retinopathy detection system, the legal, social, ethical and sustainability
aspects associated with diabetic retinopathy detection that are discussed as follows.
Social Aspects – The first main social aspect is that the patients may not agree to be
tested with a new type of technology that involves computer simulation. This is mainly because
this is a new and untested technology that have not been extensively used in any clinics. As a
result, the patients are not aware whether there are any risks with the process (Canche, Dalmau
and García 2017). The patients will never accept any clinical procedure that does not ensure that
their organs will not be further damaged. Hence, before releasing this technology for clinical use,
a lot of detailed testing and raising awareness are necessary so as to convince the patients that the
process is very safe for the clinical treatment and diagnosis. The overall testing process should
include the functionality of the system, the impact of its use on the body and organs of the
patients, any negative aspects and others. There are many medical devices that can cause
significant side effects on the patients’ bodies and hence, these types of devices are only used in
urgent situations (Majumdar et al. 2015). Moreover, the patients often do not allow the use of
devices that have side effects or the possible side effects are not known to the doctors. Once the
testing of the system is complete, it is important for the clinics and hospitals to raise awareness
so that the patients understand the working of the devices and whether they will have any
negative impact on their bodies rather than benefitting them.
Ethical Aspects – There are also ethical aspects associated with this particular technology
and it is almost similar to the social aspect. Using this untested technology with the patients’
proper knowledge or permission can raise several ethical concerns regarding the treatment
process (Krawitz et al. 2017). Again, since this is a computerised process, the personal and
clinical information of the patients need to be entered into the system and stored in the cloud
6PROJECT MANAGEMENT
database that can raise cyber security issues. Moreover, the information may be stored by the
clinic without prior permission of the patients that also raises several ethical concern regarding
the usage of the system. While implementing or using a new technology, it must be ensured that
it follows the standard ethical aspects and guidelines. Moreover, the systems that have security
threats and issues must be evaluated and protected with sufficient security before implementing
them for commercial usage. In this case, a systematic procedure needs to be followed in which
the security issues and threats must be identified. Once these security threats are identified, they
should be properly mitigated in order to ensure the chances of encountering the threats are
minimised. In this system, the threats include cyber security risk in which some external entity
may try to steal and misuse personal and medical information of the patients (Deepa, Kumar and
Andrews 2019). Hence, suitable software must be utilised to prevent any unauthorised access
such that the patients’ data is securely stored. Once the security setup is done and the system is
ready to use, the patients should be made aware regarding the benefits and the use of the system
and also the functionalities that require storing personal and medical information of the patients.
Moreover, the patients should be requested to sign an ethical agreement form through which, the
patients agree to the use of the detection system as a part of their treatment process.
Legal Aspects – The legal aspects regarding the use of this new Diabetic Retinopathy
Detection System arises from the ethical issues and concerns raised in the previous paragraph.
Unauthorized use and storage of personal and medical information of the patients can result in
severe legal issues and the patients can sue the clinics if they feel necessary (Majumdar et al.
2015). Storing and managing patient data in cloud database poses the threat of cyber security
issues and hence, the process requires prior approval of the patients. In addition, the use of the
computerized system also requires prior approval of the patients, especially in the early stages of
database that can raise cyber security issues. Moreover, the information may be stored by the
clinic without prior permission of the patients that also raises several ethical concern regarding
the usage of the system. While implementing or using a new technology, it must be ensured that
it follows the standard ethical aspects and guidelines. Moreover, the systems that have security
threats and issues must be evaluated and protected with sufficient security before implementing
them for commercial usage. In this case, a systematic procedure needs to be followed in which
the security issues and threats must be identified. Once these security threats are identified, they
should be properly mitigated in order to ensure the chances of encountering the threats are
minimised. In this system, the threats include cyber security risk in which some external entity
may try to steal and misuse personal and medical information of the patients (Deepa, Kumar and
Andrews 2019). Hence, suitable software must be utilised to prevent any unauthorised access
such that the patients’ data is securely stored. Once the security setup is done and the system is
ready to use, the patients should be made aware regarding the benefits and the use of the system
and also the functionalities that require storing personal and medical information of the patients.
Moreover, the patients should be requested to sign an ethical agreement form through which, the
patients agree to the use of the detection system as a part of their treatment process.
Legal Aspects – The legal aspects regarding the use of this new Diabetic Retinopathy
Detection System arises from the ethical issues and concerns raised in the previous paragraph.
Unauthorized use and storage of personal and medical information of the patients can result in
severe legal issues and the patients can sue the clinics if they feel necessary (Majumdar et al.
2015). Storing and managing patient data in cloud database poses the threat of cyber security
issues and hence, the process requires prior approval of the patients. In addition, the use of the
computerized system also requires prior approval of the patients, especially in the early stages of
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7PROJECT MANAGEMENT
launch as this is a new type of technology. Again, this particular system involves use of software
and software toolkits that can be of pirated versions. This again raises legal issue as it is
completely illegal to use pirated and non-licensed software in any type of commercial and non-
commercial usage. In order to ensure the legal guidelines are met and fulfilled, it is first required
to evaluate the legal hardware and software usage guidelines and agreements of the organisation
as well as the devices purchased for setting up the system. It is important to purchase hardware
and software from reliable and authorized vendors in order to avoid unnecessary legal and other
complications (Kaur and Mann 2017). Many organisations often use un-licensed and pirated
software downloaded from piracy websites like torrent in order to avoid huge amount of costs
involved in purchasing licensed versions of the software. This is an illegal process and if the
organisation gets caught in using pirated software, their business license may get cancelled in
addition to punishments for the management board. Hence, piracy and illegal resource usage
must be avoided and if some assistance is required regarding the legal aspects, a legal assistant
can be appointed. Furthermore, the use of a new medical system must be licensed before
implementing it for commercial purpose.
Sustainability Aspects – There are some sustainability aspects mainly due to this being a
new technology. The first sustainability aspect involves the design of the entire technology. It is
required to develop a design that is resource efficient in nature and also provides high value of
productivity. Again, the overall design should be durable, e.g. the software used to run the
system should be functional continuously and should not crash and show errors during use (Kaur
and Mann 2017). Furthermore, the hardware used must be degradable in nature and environment
friendly so as to avoid any negative impact on the environment. Finally, the main sustainability
aspect is that the entire technology implementation and maintenance process must be cost
launch as this is a new type of technology. Again, this particular system involves use of software
and software toolkits that can be of pirated versions. This again raises legal issue as it is
completely illegal to use pirated and non-licensed software in any type of commercial and non-
commercial usage. In order to ensure the legal guidelines are met and fulfilled, it is first required
to evaluate the legal hardware and software usage guidelines and agreements of the organisation
as well as the devices purchased for setting up the system. It is important to purchase hardware
and software from reliable and authorized vendors in order to avoid unnecessary legal and other
complications (Kaur and Mann 2017). Many organisations often use un-licensed and pirated
software downloaded from piracy websites like torrent in order to avoid huge amount of costs
involved in purchasing licensed versions of the software. This is an illegal process and if the
organisation gets caught in using pirated software, their business license may get cancelled in
addition to punishments for the management board. Hence, piracy and illegal resource usage
must be avoided and if some assistance is required regarding the legal aspects, a legal assistant
can be appointed. Furthermore, the use of a new medical system must be licensed before
implementing it for commercial purpose.
Sustainability Aspects – There are some sustainability aspects mainly due to this being a
new technology. The first sustainability aspect involves the design of the entire technology. It is
required to develop a design that is resource efficient in nature and also provides high value of
productivity. Again, the overall design should be durable, e.g. the software used to run the
system should be functional continuously and should not crash and show errors during use (Kaur
and Mann 2017). Furthermore, the hardware used must be degradable in nature and environment
friendly so as to avoid any negative impact on the environment. Finally, the main sustainability
aspect is that the entire technology implementation and maintenance process must be cost
8PROJECT MANAGEMENT
effective for all eye testing clinics. Sustainability is an important aspect of any new technology
or implementation that ensures it will provide financial and non-financial benefits to the
organisation for a considerable period of time. In addition to the internal benefits, it is also
important that the new technology or sustainable for the environment and does not create any
harmful impact on the same (Bhaduri et al. 2017). On the other hand, the technological resources
that can be used for a long amount of time and also do not harm the environment when disposed
are called environmentally sustainable and are recommended for use.
effective for all eye testing clinics. Sustainability is an important aspect of any new technology
or implementation that ensures it will provide financial and non-financial benefits to the
organisation for a considerable period of time. In addition to the internal benefits, it is also
important that the new technology or sustainable for the environment and does not create any
harmful impact on the same (Bhaduri et al. 2017). On the other hand, the technological resources
that can be used for a long amount of time and also do not harm the environment when disposed
are called environmentally sustainable and are recommended for use.
9PROJECT MANAGEMENT
References
Bahadar Khan, K., Khaliq, A.A. and Shahid, M., 2016. A morphological hessian based approach
for retinal blood vessels segmentation and denoising using region based otsu thresholding. PloS
one, 11(7), p.e0158996.
Bhaduri, B., Shelton, R.L., Nolan, R.M., Hendren, L., Almasov, A., Labriola, L.T. and Boppart,
S.A., 2017. Ratiometric analysis of optical coherence tomography–measured in vivo retinal layer
thicknesses for the detection of early diabetic retinopathy. Journal of biophotonics, 10(11),
pp.1430-1441.
Canche, M., Dalmau, O. and García, M., 2017, October. Automatic Detection of Hard Exudates
in Retinal Images with Diabetic Retinopathy. In 2017 Sixteenth Mexican International
Conference on Artificial Intelligence (MICAI) (pp. 53-59). IEEE.
Chui, T.Y.P., Pinhas, A., Gan, A., Razeen, M., Shah, N., Cheang, E., Liu, C.L., Dubra, A. and
Rosen, R.B., 2016. Longitudinal imaging of microvascular remodelling in proliferative diabetic
retinopathy using adaptive optics scanning light ophthalmoscopy. Ophthalmic and Physiological
Optics, 36(3), pp.290-302.
Deepa, V., Kumar, C.S. and Andrews, S.S., 2019. Automated detection of microaneurysms using
Stockwell transform and statistical features. IET Image Processing, 13(8), pp.1341-1348.
Kaur, S. and Mann, K.S., 2017. Optimized retinal blood vessel segmentation technique for
detection of diabetic retinopathy. International Journal of Advanced Research in Computer
Science, 8(9).
References
Bahadar Khan, K., Khaliq, A.A. and Shahid, M., 2016. A morphological hessian based approach
for retinal blood vessels segmentation and denoising using region based otsu thresholding. PloS
one, 11(7), p.e0158996.
Bhaduri, B., Shelton, R.L., Nolan, R.M., Hendren, L., Almasov, A., Labriola, L.T. and Boppart,
S.A., 2017. Ratiometric analysis of optical coherence tomography–measured in vivo retinal layer
thicknesses for the detection of early diabetic retinopathy. Journal of biophotonics, 10(11),
pp.1430-1441.
Canche, M., Dalmau, O. and García, M., 2017, October. Automatic Detection of Hard Exudates
in Retinal Images with Diabetic Retinopathy. In 2017 Sixteenth Mexican International
Conference on Artificial Intelligence (MICAI) (pp. 53-59). IEEE.
Chui, T.Y.P., Pinhas, A., Gan, A., Razeen, M., Shah, N., Cheang, E., Liu, C.L., Dubra, A. and
Rosen, R.B., 2016. Longitudinal imaging of microvascular remodelling in proliferative diabetic
retinopathy using adaptive optics scanning light ophthalmoscopy. Ophthalmic and Physiological
Optics, 36(3), pp.290-302.
Deepa, V., Kumar, C.S. and Andrews, S.S., 2019. Automated detection of microaneurysms using
Stockwell transform and statistical features. IET Image Processing, 13(8), pp.1341-1348.
Kaur, S. and Mann, K.S., 2017. Optimized retinal blood vessel segmentation technique for
detection of diabetic retinopathy. International Journal of Advanced Research in Computer
Science, 8(9).
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10PROJECT MANAGEMENT
Kim, A.Y., Chu, Z., Shahidzadeh, A., Wang, R.K., Puliafito, C.A. and Kashani, A.H., 2016.
Quantifying microvascular density and morphology in diabetic retinopathy using spectral-
domain optical coherence tomography angiography. Investigative ophthalmology & visual
science, 57(9), pp.OCT362-OCT370.
Krawitz, B.D., Mo, S., Geyman, L.S., Agemy, S.A., Scripsema, N.K., Garcia, P.M., Chui, T.Y.
and Rosen, R.B., 2017. Acircularity index and axis ratio of the foveal avascular zone in diabetic
eyes and healthy controls measured by optical coherence tomography angiography. Vision
research, 139, pp.177-186.
Majumdar, J., Tewary, S., Chakraborty, S., Kundu, D., Ghosh, S. and Gupta, S.D., 2015. An
Automated Graphical User Interface based System for the Extraction of Retinal Blood Vessels
using Kirsch's Template. International Journal Of Advanced Computer Science And
Applications, 6(6), pp.86-93.
Mazumder, A.G., Banerjee, S., Zevictovich, F., Ghosh, S., Mukherjee, A. and Chatterjee, J.,
2018. Fourier-transform-infrared-spectroscopy based metabolomic spectral biomarker selection
towards optimal diagnostic differentiation of diabetes with and without
retinopathy. Spectroscopy Letters, 51(7), pp.340-349.
Tan, J.H., Acharya, U.R., Bhandary, S.V., Chua, K.C. and Sivaprasad, S., 2017. Segmentation of
optic disc, fovea and retinal vasculature using a single convolutional neural network. Journal of
Computational Science, 20, pp.70-79.
Tan, J.H., Fujita, H., Sivaprasad, S., Bhandary, S.V., Rao, A.K., Chua, K.C. and Acharya, U.R.,
2017. Automated segmentation of exudates, haemorrhages, microaneurysms using single
convolutional neural network. Information sciences, 420, pp.66-76.
Kim, A.Y., Chu, Z., Shahidzadeh, A., Wang, R.K., Puliafito, C.A. and Kashani, A.H., 2016.
Quantifying microvascular density and morphology in diabetic retinopathy using spectral-
domain optical coherence tomography angiography. Investigative ophthalmology & visual
science, 57(9), pp.OCT362-OCT370.
Krawitz, B.D., Mo, S., Geyman, L.S., Agemy, S.A., Scripsema, N.K., Garcia, P.M., Chui, T.Y.
and Rosen, R.B., 2017. Acircularity index and axis ratio of the foveal avascular zone in diabetic
eyes and healthy controls measured by optical coherence tomography angiography. Vision
research, 139, pp.177-186.
Majumdar, J., Tewary, S., Chakraborty, S., Kundu, D., Ghosh, S. and Gupta, S.D., 2015. An
Automated Graphical User Interface based System for the Extraction of Retinal Blood Vessels
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