Nahida Akter

PhD Candidate

Research Title: Automated Detection of Ocular Disease with Artificial Intelligence


Dr Maitreyee Roy


Professor John Fletcher, School of Electrical Engineering and Telecommunications


A/Professor Stuart Perry, School of Electrical and Data Engineering, UTS


Dr Jack Phu, Lead Clinician, Centre for Eye Health (CFEH), UNSW

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Currently artificial intelligence (AI), especially deep learning (DL), techniques are revolutionising healthcare for its potential in image-based diagnosis, disease-prognostication, and risk-assessment. In ophthalmology, AI is also becoming common for screening, image-interpretation, early diagnosis and guiding treatment of eye conditions. This project will highlight new research directions and examine the main challenges of machine learning in ophthalmology, such as the “black box” problem which decreases clinical reliability and algorithm transparency of AI in healthcare. This research will devise and evaluate new clinically meaningful metrics for analysing ocular images, implement novel DL algorithms for automatic segmentation, disease detection and progression-classification of eye diseases using both fundus photographs and optical coherence tomography (OCT) images from both healthy subjects and patients undergoing treatment for eye disease.

The project currently focuses on glaucoma as diseases like age-related macular degeneration, retinopathy of prematurity and diabetic retinopathy have well-defined lesions visible on fundus photography and other en face techniques e.g., image analysis and AI spaces. AI has shown great promise in classifying 2D images by distinguishing noticeable features occurring in glaucoma such as enlarged cup-disc-ratio. However, a challenge remains regarding reaching the performance of expert clinicians in a real-world clinical pathway with three-dimensional diagnostic scans and accumulation of patient’s clinical history manifests the AI system more reliable and trustworthy.

We initially aimed to improve our understanding, screening and detection of glaucoma progression using both 2D and 3D fundus, OCT retinal images. Multiple feature extraction techniques, classification methods and DL techniques will then be designed, implemented and tested for the purpose of diagnosis of glaucoma. Finally, the same model will be applied in diagnosing other diseases as well.


Experienced more than 5 years as a professional in Engineering field with a demonstrated history of working in the industry and higher education institute. Skilled in 3D Unity, MATLAB, Python, SPSS, Web Design and Computer Networking. Currently working with Artificial Intelligence as a PhD research student of Optical Imaging and Visualization (OIV) Lab, SOVS, UNSW Sydney, Australia.


MSc. in Telecommunication Engineering (2018)

BSc. in Computer Science and Telecommunication Engineering (2012)

Noakhali Science & Technology University (NSTU), Bangladesh


Journal Articles

  1. Akter N (Corresponding Author), Nobi A. Investigation of Financial Stability of S&P500 Using Realized Volatility and Stock Returns Distribution. Journal of Risk and Financial Management, 2018; 11(2):22.
  2. Yeasmin M, Akter N (Corresponding Author), Kabir MH, Hossain MJ. Performance evaluation of multi cloud compared to the single-cloud under varying Firewall conditions. Cogent Engineering, 2018; 5: 1471974.
  3. Billah MM, Rana SMM, Akter N, Hossain MS. Analysis of serum electrolyte and lipid profile in young Bangladeshi female with Type II Diabetes. Cogent Biology, 2018; 4:1431474.
  4. Shahabuddin AA, Shalu PD, Akter N (Corresponding Author). Optimized Process Design of RF Energy Harvesting Circuit for Low Power Devices. International Journal of Applied Engineering Research, 2018; 13(2): 849-854.
  5. Akter N (Corresponding Author), Hossain MB, Kabir MH, Hossain A, Yeasmin M, Sultana S. Design & Performance Analysis of 10 stage Voltage Doublers RF Energy Harvesting Circuit for Wireless Sensor Network. Journal of Communications Engineering and Networks, 2014; 2(2): 8491.  


Best overall Poster Award, UNSW Science Postgraduate Research Showcase 2019

University International Postgraduate Award (UIPA), UNSW Sydney, Australia

Undergraduate Academic Merit Scholarship (2008-2012), NSTU, Bangladesh


  1. Akter N, Phu J, Perry S, Fletcher J, Kalloniatis M, and Roy M, “Analysis of OCT Images to Optimize Glaucoma Diagnosis”, Imaging and Applied Optics Congress, 24-27 June 2019 in Munich, Germany, accepted 14th March 2019 (Oral)
  2. Akter N, Li A, Shi R, Phu J, Perry S, Fletcher J, and Roy M, “A feature agnostic based glaucoma diagnosis from OCT images with deep learning technique” American Academy of Optometry, 23-27 October 2019, Orlando, America, accepted 19th July 2019 (Oral)


  1. Assistant Professor, Dept. of Computer Science and Telecommunication Engineering, NSTU, Bangladesh (Study leave)
  2. Intern, Perceptual Imaging Lab. School of Electrical and Data Engineering, University Technology Sydney (March 05, 2018 to June 05, 2018)