Staff profile

Please check out my personal webpage for more information.

Rahele Kafieh is an Assistant Professor of Bioengineering at Durham University and an EPSRC Women in Engineering Ambassador. Her research focuses on using Artificial Intelligence (AI) for biomedical image and signal processing. She collaborates closely with clinicians and the NHS on initiatives aimed at the early diagnosis of disease, enabling home-based imaging for elderly populations, and streamlining AI-powered referral systems from the community to hospitals. With over 13 years of experience in medical data processing using AI, more than 120 research publications, and over 4,275 citations, she has secured funding from a range of national and international sources.

Research Funding

Rahele's research funding spans AI-enabled ocular and neuro-imaging, home-based diagnostic monitoring, signal and image processing, and interdisciplinary environmental sensing, with awards from EPSRC, MRC, UKRI, the Dunhill Medical Trust, Durham University, and international funders including TÜBİTAK, NIMAD, Einstein Forum, and the Iran–Switzerland Research Seed Fund, in roles as both Principal Investigator and Co-Investigator.

AI and Optical Coherence Tomography for Eye Health

• A Pilot Study to Deliver Healthcare Innovation for Diabetic Eye Disease in the North East — EPSRC IAA, Co-I (2025)
• EYESAVE: AI-enabled triage for Glaucoma — The Dunhill Medical Trust (Age-related Hearing & Vision programme), Co-I (2025)
• Enhancing Healthcare with AI-Based Home Monitoring for Retinal Diseases — EPSRC IAA, PI (2024)
• OCTage: monitoring the ageing brain via Optical Coherence Tomography of the eyes (MR/Y010825/1) — UKRI-MRC, Co-I (2023)
• A Feasibility Study to Develop an OCT-Based Ocular Health Kiosk to Diagnose Diabetic Retinopathy — Iran–Switzerland Research Seed Fund, Co-I (2018)

Neurodegenerative Disease Screening

• Deep Learning-Based Image and Blink-Rate Analysis, and Tear Protein Detection for Effective PD and PSP Screening — MRC IAA, Co-I (2024)
• Deep Learning Models with OCT and MRI Data in Autoimmune Neuroinflammatory Disorders — Einstein Forum, PI (2018)
• Automatic Analysis of MRI and OCT Data for Discrimination of Multiple Sclerosis (MS) and Neuromyelitis Optica (NMO) in the Presence of Isolated Optic Neuritis — National Institute for Medical Research Development (NIMAD), PI (2018)

Wireless Systems, Signal and Image Processing

• Recyclable Chipless RFID: Bridging Sustainable Materials with Electromagnetic Innovation for Circular Economy Wireless Systems — EPSRC IAA, Co-I (2026)
• Design and Application of Bandlet on Graph for Image Denoising — TÜBİTAK, PI (2014)
• Non-Destructive Quality Testing of Polyethylene Pipe Welding Using Thermal Infrared Imaging — National Iranian Gas Company, Co-I (2014)

Environmental and Interdisciplinary Research

• NemBio: Understanding the Functional Role of Nematodes in Degraded Terrestrial Polluted Environments — Durham Seedcorn, Co-I (2025)
• Strategic Research Fund: SMART Soils Lab (Soil and Microbiome Augmentation and Restoration Technologies Lab) — Co-I (2023)

Other

• Global Engagement Grant — PI (2024)

Honors and Awards

• EPSRC Women in Engineering Ambassador
• Recognised with the "Exceptionally Good Review" award by Translational Vision Science & Technology for an outstanding peer review, 2026.

• Medical Data Analysis
• Machine learning / Deep Learning
• Image Processing and Computer Vision
• Time-frequency methods
• Data Acquisition and Management
• Data Quality Assessment

• 2026: Recognised with the "Exceptionally Good Review" award by Translational Vision Science & Technology for an outstanding peer review.:
• 2026 - 2029: External Examiner, University of West London: External quality assurance of MSc modules in AI, Machine Learning, Deep Learning, Responsible AI, Data Science, Computer Science, Software Engineering, Cyber Security, and Health Informatics.:
• 2026: External Adviser, University of West London: Provided independent academic review and quality assurance for the design and approval of the MSc Computer Science and BSc (Hons) Business Computing programmes, evaluating curriculum, module specifications, learning outcomes, and assessment strategies against UK higher education standards.:
• 2025: Member of MRC/NIHR Liaison Group, Durham University.:
• 2023: Advisory Panel Member at Siloton:
• 2023: Invited talk in UK Metamaterial Network:
• 2023: Invited talk: 4th annual vision and colour summer data blast optica technical groups:
• 2023: Invited talk in International Webinar on Image Analysis in Ophthalmology by Appraise:
• 2023: Invited talk in DEMON Network: "Artificial Intelligence in Eye imaging: An easy-to-use mirror of brain-related abnormalities in Dementia"
• 2022: Invited talk in Turing Network Development Award at QUB - AIQ Seminar on Ophthalmic Imaging:
• 2022: Invited talk on 'Machine learning in Healthcare' in Institute of Physics (IOP), London:
• 2022: Topic editor: in Artificial Intelligence in Cancer Diagnosis and Therapy:
• 2022: Guest Editor: in Advances in Optical Coherence Tomography Angiography (Diagnostics):
• 2020: Editorial Board Member of the 11 Iranian and the first International Conference on Machine Vision and Image Processing (MVIP) (2020):
• 2018 - 2023: Section Editor in Journal of Medical Signals and Sensors (JMSS):
• 2010: Director of Student Committee in 17th Iranian Biomedical Engineering Conference (ICBME’17) (2010):
• 2007: Head of Biomedical engineering Section in 10th Iranian Student Conference on EE (ISCEE’07) (2007):

Chapter in book

• Introduction to Optical Coherence Tomography
  
  Hajizadeh, F., Kafieh, R., & Tajmirriahi, M. (2023). Introduction to Optical Coherence Tomography. In F. Hajizadeh (Ed.), Atlas of Ocular Optical Coherence Tomography (2nd ed., pp. 1-34). Springer Verlag. https://doi.org/10.1007/978-3-031-07410-3_1
• Application of enface image registration/alignment to introduce new ocular imaging biomarkers
  
  Amini, Z., Kafieh, R., Tajmirriahi, M., Parsons, Z., & Rabbani, H. (2022). Application of enface image registration/alignment to introduce new ocular imaging biomarkers. In Photo Acoustic and Optical Coherence Tomography Imaging, Volume 2 (pp. 3-1-3-23). IOP Publishing. https://doi.org/10.1088/978-0-7503-2056-6ch3

Conference Paper

• Recursive autoencoder network for prediction of CAD model parameters from STEP files
  
  Miles, V., Giani, S., Vogt, O., & Kafieh, R. (2024). Recursive autoencoder network for prediction of CAD model parameters from STEP files. Procedia Computer Science, 232, 3239-3246. https://doi.org/10.1016/j.procs.2024.02.139
• Determination of Foveal Avascular Zone Parameters Using a New Location-Aware Deep-Learning Method.
  
  Sobhaninia, Z., Danesh, H., Kafieh, R., Balaji, J. J., & Lakshminarayanan, V. (2021). Determination of Foveal Avascular Zone Parameters Using a New Location-Aware Deep-Learning Method. In M. Zelinski, T. Taha, & J. Howe (Eds.), Proceedings of SPIE. https://doi.org/10.1117/12.2594152
• OCT Image Denoising Based on Asymmetric Normal Laplace Mixture Model
  
  Jorjandi, S., Rabbani, H., Amini, Z., & Kafieh, R. (2019). OCT Image Denoising Based on Asymmetric Normal Laplace Mixture Model. In IEEE Engineering in Medicine and Biology Society Conference Proceedings (pp. 2679-2682).
• Statistical Modeling of Optical Coherence Tomography Images by Asymmetric Normal Laplace Mixture Model
  
  Jorjandi, S., Rabbani, H., Kafieh, R., & Amini, Z. (2017). Statistical Modeling of Optical Coherence Tomography Images by Asymmetric Normal Laplace Mixture Model. In PROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (pp. 4399-4402).
• Exact Localization of Breakpoints of Retinal Pigment Epithelium in Optical Coherence Tomography of Optic Nerve Head
  
  Mokhtari, M., Rabbani, H., Mehri-Dehnavi, A., & Kafieh, R. (2017). Exact Localization of Breakpoints of Retinal Pigment Epithelium in Optical Coherence Tomography of Optic Nerve Head. In PROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (pp. 1505-1508).
• ASYMMETRY EVALUATION OF FUNDUS IMAGES IN RIGHT AND LEFT EYES USING RADON TRANSFORM AND FRACTAL ANALYSIS
  
  Mahmudi, T., Kafieh, R., Rabbani, H., Mehri, A., & Akhlagi, M. (2015). ASYMMETRY EVALUATION OF FUNDUS IMAGES IN RIGHT AND LEFT EYES USING RADON TRANSFORM AND FRACTAL ANALYSIS. In IEEE International Conference on Image Processing ICIP (pp. 163-167).
• Comparison of macular OCTs in right and left eyes of normal people
  
  Mahmudi, T., Kafieh, R., Rabbani, H., Dehnavi, A. M., & Akhlagi, M. (2014). Comparison of macular OCTs in right and left eyes of normal people. In R. Molthen & J. Weaver (Eds.), Proceedings of SPIE. https://doi.org/10.1117/12.2044046
• Combination of Graph Theoretic Grouping and Time-Frequency Analysis for Image Segmentation
  
  Kafieh, R., Rabbani, H., & Gazor, S. (2014). Combination of Graph Theoretic Grouping and Time-Frequency Analysis for Image Segmentation. In International Conference on Acoustics Speech and Signal Processing ICASSP.
• Optical Coherence Tomography Noise Reduction Over Learned Dictionaries with Introduction of Complex Wavelet for start dictionary
  
  Kafieh, R., & Rabbani, H. (2013). Optical Coherence Tomography Noise Reduction Over Learned Dictionaries with Introduction of Complex Wavelet for start dictionary. In D. VanDeVille, V. Goyal, & M. Papadakis (Eds.), Proceedings of SPIE. https://doi.org/10.1117/12.2026520
• VESSEL SEGMENTATION IN IMAGES OF OPTICAL COHERENCE TOMOGRAPHY USING SHADOW INFORMATION AND THICKENING OF RETINAL NERVE FIBER LAYER
  
  Kafieh, R., Danesh, H., Rabbani, H., Abramoff, M., & Sonka, M. (2013). VESSEL SEGMENTATION IN IMAGES OF OPTICAL COHERENCE TOMOGRAPHY USING SHADOW INFORMATION AND THICKENING OF RETINAL NERVE FIBER LAYER. In International Conference on Acoustics Speech and Signal Processing ICASSP (pp. 1075-1079).
• INTRA-RETINAL LAYER SEGMENTATION OF OPTICAL COHERENCE TOMOGRAPHY USING DIFFUSION MAP
  
  Kafieh, R., Rabbani, H., Abramoff, M., & Sonka, M. (2013). INTRA-RETINAL LAYER SEGMENTATION OF OPTICAL COHERENCE TOMOGRAPHY USING DIFFUSION MAP. In International Conference on Acoustics Speech and Signal Processing ICASSP (pp. 1080-1084).
• OCT Image Alignment Using Diffusion Maps
  
  Kafieh, R., Rabbani, H., Abramoff, M. D., & Sonka, M. (2012). OCT Image Alignment Using Diffusion Maps. In D. Haynor & S. Ourselin (Eds.), Proceedings of SPIE. https://doi.org/10.1117/12.912259
• Circular symmetric Laplacian mixture model in wavelet diffusion for dental image denoising
  
  Kafieh, R., Rabbani, H., & Foroohandeh, M. (2012). Circular symmetric Laplacian mixture model in wavelet diffusion for dental image denoising. In D. Haynor & S. Ourselin (Eds.), Proceedings of SPIE. https://doi.org/10.1117/12.911065
• WAVELET-BASED MEDICAL INFRARED IMAGE NOISE REDUCTION USING LOCAL MODEL FOR SIGNAL AND NOISE
  
  Kafieh, R., & Rabbani, H. (2011). WAVELET-BASED MEDICAL INFRARED IMAGE NOISE REDUCTION USING LOCAL MODEL FOR SIGNAL AND NOISE. Presented at 2011 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP) IEEE.
• Discrimination of Bony Structures in Cephalograms for Automatic Landmark Detection
  
  Kafieh, R., Sadri, S., Mehri, A., & Raji, H. (2008). Discrimination of Bony Structures in Cephalograms for Automatic Landmark Detection. In H. Sarbazi-Azad, B. Parhami, S. Miremadi, & S. Hessabi (Eds.), Communications in Computer and Information Science.
• Detection of ventricular arrhythmias using roots location in AR-modelling
  
  Kafieh, R., Mehri, A., & Amirfattahi, R. (2007). Detection of ventricular arrhythmias using roots location in AR-modelling. Presented at 2007 6TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATIONS \& SIGNAL PROCESSING, VOLS 1-4.
• Using a combination of model based and intelligent methods in automatic landmark detection in cephalometry
  
  Kafieh, R., Sadri, S., mehri, A., & Raji, H. (2007). Using a combination of model based and intelligent methods in automatic landmark detection in cephalometry. Presented at 2007 INNOVATIONS IN INFORMATION TECHNOLOGIES, VOLS 1 AND 2 IEEE.
• Automatic landmark detection in-cephalometry using a modified active shape model with sub image matching
  
  Kafieh, R., mehri, A., & sadri, S. (2007). Automatic landmark detection in-cephalometry using a modified active shape model with sub image matching. Presented at INTERNATIONAL CONFERENCE ON MACHINE VISION 2007, PROCEEDINGS Coll Signals; Natl Univ Sci \& Technol.

Edited book

• Artificial Intelligence in Cancer Diagnosis and Therapy
  
  Khayyam, H., Madani, A., Kafieh, R., & Hekmatnia, A. (Eds.). (2023). Artificial Intelligence in Cancer Diagnosis and Therapy. MDPI.

Journal Article

• Deep Learning-Based Diagnostic Classification of Multiple Sclerosis Using Multicenter Optical Coherence Tomography Data
  
  Khodabandeh, Z., Rabbani, H., Shirani Bidabadi, N., Ashtari, F., Steel, D. H., Bacardit, J., Hurlbert, A., & Kafieh, R. (2026). Deep Learning-Based Diagnostic Classification of Multiple Sclerosis Using Multicenter Optical Coherence Tomography Data. Experimental Eye Research, 266, Article 110916. https://doi.org/10.1016/j.exer.2026.110916
• The Application of a Deep Learning Algorithm for the Segmentation of Retinal Nerve Fiber Layer Across Different Optic Neuropathies
  
  Arian, R., Behzadi Far, M., Sadeghi, R., Farnaghi, F., Safizadeh, M., Subramanian, P. S., Miller, N. R., Suwan, Y., Kajornrojanaruk, P., Kafieh, R., & Aghsaei Fard, M. (2026). The Application of a Deep Learning Algorithm for the Segmentation of Retinal Nerve Fiber Layer Across Different Optic Neuropathies. Translational Vision Science & Technology, 15(4), Article 7. https://doi.org/10.1167/tvst.15.4.7
• A Functional Shape Framework for the Detection of Multiple Sclerosis Using Optical Coherence Tomography Images
  
  Tahvilian, H., Kafieh, R., Ashtari, F., Swamy, M. N. S., & Ahmad, M. O. (2026). A Functional Shape Framework for the Detection of Multiple Sclerosis Using Optical Coherence Tomography Images. Sensors, 26(8), Article 2399. https://doi.org/10.3390/s26082399
• Lessons Learned: Quality Analysis of Optical Coherence Tomography in Neuromyelitis Optica
  
  Salih, H., Samadzadeh, S., Bereuter, C., Motamedi, S., Chien, C., Villoslada, P., Stiebel‐Kalish, H., Asgari, N., Mao‐Draayer, Y., Ringelstein, M., Havla, J., Peixoto, M. A. L., Kim, H. J., Palace, J., Leite, M. I., Sharma, S. M., Ashtari, F., Kafieh, R., Pandit, L., … Zimmermann, H. G. (2026). Lessons Learned: Quality Analysis of Optical Coherence Tomography in Neuromyelitis Optica. Annals of Clinical and Translational Neurology, 13(3), 427-642. https://doi.org/10.1002/acn3.70235
• Automatic assessment of lung involvement in systemic sclerosis using deep learning
  
  Esnaashari, M., Arian, R., Hajihashemi, A., Saeedizadeh, N., Hajiahmadi, S., Sadeghi, S., Shayganfar, A., & Kafieh, R. (2026). Automatic assessment of lung involvement in systemic sclerosis using deep learning. Journal of Research in Medical Sciences, 31(2), Article 10. https://doi.org/10.4103/jrms.jrms_994_25
• Corpus Callosum Indices are Correlated with Disability and Cognitive Performance in Patients with Multiple Sclerosis: A Systematic Review and Meta-Analysis
  
  Tabibian, F., Hoseini, E., Motahharynia, A., Azimzadeh, K., Kafieh, R., Amini, Z., & Adibi, I. (2025). Corpus Callosum Indices are Correlated with Disability and Cognitive Performance in Patients with Multiple Sclerosis: A Systematic Review and Meta-Analysis. Multiple Sclerosis and Related Disorders, 100, Article 106522. https://doi.org/10.1016/j.msard.2025.106522
• Analyzing Retinal Vessel Morphology in MS Using Interpretable AI on Deep Learning-Segmented IR-SLO Images
  
  Soltanipour, A., Arian, R., Aghababaei, A., Ashtari, F., Zhou, Y., Keane, P. A., & Kafieh, R. (2025). Analyzing Retinal Vessel Morphology in MS Using Interpretable AI on Deep Learning-Segmented IR-SLO Images. Bioengineering, 12(8), Article 847. https://doi.org/10.3390/bioengineering12080847
• Association of myopia and parapapillary choroidal microvascular density in primary open-angle glaucoma
  
  Suwan, Y., Chansangpetch, S., Fard, M. A., Pooprasert, P., Chalardsakul, K., Threetong, T., Tipparut, S., Saaensupho, T., Tantraworasin, A., Hojati, S., Kafieh, R., Danesh, H., Petpiroon, P., & Supakontanasan, W. (2025). Association of myopia and parapapillary choroidal microvascular density in primary open-angle glaucoma. PLOS ONE, 20(2), Article e0317881. https://doi.org/10.1371/journal.pone.0317881
• Association of peripapillary retinal nerve fiber layer atrophy with cognitive impairment in patients with neuromyelitis optica spectrum disorder.
  
  Barzegar, M., Ashtari, F., Kafieh, R., Karimi, Z., Dehghani, A., Ghalamkari, A., Afshari-Safavi, A., & Paul, F. (2025). Association of peripapillary retinal nerve fiber layer atrophy with cognitive impairment in patients with neuromyelitis optica spectrum disorder. Neurological Sciences, 46(2), 861-870. https://doi.org/10.1007/s10072-024-07897-8
• Insights from the eyes: a systematic review and meta-analysis of the intersection between eye-tracking and artificial intelligence in dementia.
  
  Norouzi, M., Kafieh, R., Chazot, P., Smith, D. T., & Amini, Z. (2025). Insights from the eyes: a systematic review and meta-analysis of the intersection between eye-tracking and artificial intelligence in dementia. Aging & Mental Health, 29(8), 1367-1375. https://doi.org/10.1080/13607863.2025.2464704
• STRIKE-MS: Synergistic Texture and Raw Intensity Knowledge Extraction for Active MS Lesion Detection on Non-Contrast MRI
  
  Amini, A., Shayganfar, A., Amini, Z., Ostovar, L., HajiAhmadi, S., Chitsaz, N., Rabbani, M., & Kafieh, R. (2025). STRIKE-MS: Synergistic Texture and Raw Intensity Knowledge Extraction for Active MS Lesion Detection on Non-Contrast MRI. IEEE Access, 13, 166452-166472. https://doi.org/10.1109/access.2025.3609133
• Application of Artificial Intelligence in Ophthalmology: An Updated Comprehensive Review.
  
  Hashemian, H., Peto, T., Ambrósio, R., Lengyel, I., Kafieh, R., Muhammed Noori, A., & Khorrami-Nejad, M. (2024). Application of Artificial Intelligence in Ophthalmology: An Updated Comprehensive Review. Journal of Ophthalmic and Vision Research, 19(3), 354-367. https://doi.org/10.18502/jovr.v19i3.15893
• Discrimination of multiple sclerosis using scanning laser ophthalmoscopy images with autoencoder-based feature extraction
  
  Aghababaei, A., Arian, R., Soltanipour, A., Ashtari, F., Rabbani, H., & Kafieh, R. (2024). Discrimination of multiple sclerosis using scanning laser ophthalmoscopy images with autoencoder-based feature extraction. Multiple Sclerosis and Related Disorders, 88, Article 105743. https://doi.org/10.1016/j.msard.2024.105743
• SLO-Net: Enhancing Multiple Sclerosis Diagnosis Beyond Optical Coherence Tomography Using Infrared Reflectance Scanning Laser Ophthalmoscopy Images.
  
  Arian, R., Aghababaei, A., Soltanipour, A., Khodabandeh, Z., Rakhshani, S., Iyer, S. B., Ashtari, F., Rabbani, H., & Kafieh, R. (2024). SLO-Net: Enhancing Multiple Sclerosis Diagnosis Beyond Optical Coherence Tomography Using Infrared Reflectance Scanning Laser Ophthalmoscopy Images. Translational Vision Science & Technology, 13(7), Article 13. https://doi.org/10.1167/tvst.13.7.13
• Deep learning for discrimination of active and inactive lesions in multiple sclerosis using non-contrast FLAIR MRI: A multicenter study.
  
  Amini, A., Shayganfar, A., Amini, Z., Ostovar, L., HajiAhmadi, S., Chitsaz, N., Rabbani, M., & Kafieh, R. (2024). Deep learning for discrimination of active and inactive lesions in multiple sclerosis using non-contrast FLAIR MRI: A multicenter study. Multiple Sclerosis and Related Disorders, 87, Article 105642. https://doi.org/10.1016/j.msard.2024.105642
• Diagnosis of multiple sclerosis by detecting asymmetry within the retina using a similarity-based neural network
  
  Bolton, R. C., Kafieh, R., Ashtari, F., & Atapour-Abarghouei, A. (2024). Diagnosis of multiple sclerosis by detecting asymmetry within the retina using a similarity-based neural network. IEEE Access, 12, 62975-62985. https://doi.org/10.1109/access.2024.3395995
• Application of ImageJ in Optical Coherence Tomography Angiography (OCT-A): A Literature Review
  
  Rahimi, M., Khameneh, E. A., Riazi-Esfahani, H., Mahmoudi, T., Khalili Pour, E., & Kafieh, R. (2023). Application of ImageJ in Optical Coherence Tomography Angiography (OCT-A): A Literature Review. Journal of Ophthalmology, 2023. https://doi.org/10.1155/2023/9479183
• Parapapillary choroidal microvascular density in acute primary angle-closure and primary open-angle glaucoma: an optical coherence tomography angiography study
  
  Suwan, Y., Aghsaei Fard, M., Vilainerun, N., Petpiroon, P., Tantraworasin, A., Teekhasaenee, C., Ritch, R., Kafieh, R., Hojati, S., & Supakontanasan, W. (2023). Parapapillary choroidal microvascular density in acute primary angle-closure and primary open-angle glaucoma: an optical coherence tomography angiography study. British Journal of Ophthalmology, 107(10), 1438-1443. https://doi.org/10.1136/bjo-2021-321022
• Loss-Modified Transformer-Based U-Net for Accurate Segmentation of Fluids in Optical Coherence Tomography Images of Retinal Diseases.
  
  Darooei, R., Nazari, M., Kafieh, R., & Rabbani, H. (2023). Loss-Modified Transformer-Based U-Net for Accurate Segmentation of Fluids in Optical Coherence Tomography Images of Retinal Diseases. Journal of Medical Signals and Sensors, 13(4), 253-260. https://doi.org/10.4103/jmss.jmss_52_22
• Differentiating Glaucomatous Optic Neuropathy from Non-Glaucomatous Optic Neuropathies Using Deep Learning Algorithms
  
  Vali, M., Mohammadi, M., Zarei, N., Samadi, M., Atapour-Abarghouei, A., Supakontanasan, W., Suwan, Y., Subramanian, P. S., Miller, N. R., Kafieh, R., & Fard, M. A. (2023). Differentiating Glaucomatous Optic Neuropathy from Non-Glaucomatous Optic Neuropathies Using Deep Learning Algorithms. American Journal of Ophthalmology, 252, 1-8. https://doi.org/10.1016/j.ajo.2023.02.016
• Biased Deep Learning Methods in Detection of COVID-19 Using CT Images: A Challenge Mounted by Subject-Wise-Split ISFCT Dataset
  
  Parsarad, S., Saeedizadeh, N., Soufi, G. J., Shafieyoon, S., Hekmatnia, F., Zarei, A. P., Soleimany, S., Yousefi, A., Nazari, H., Torabi, P., S. Milani, A., Madani Tonekaboni, S. A., Rabbani, H., Hekmatnia, A., & Kafieh, R. (2023). Biased Deep Learning Methods in Detection of COVID-19 Using CT Images: A Challenge Mounted by Subject-Wise-Split ISFCT Dataset. Journal of Imaging, 9(8), Article 159. https://doi.org/10.3390/jimaging9080159
• Discrimination of multiple sclerosis using OCT images from two different centers
  
  Khodabandeh, Z., Rabbani, H., Ashtari, F., Zimmermann, H. G., Motamedi, S., Brandt, A. U., Paul, F., & Kafieh, R. (2023). Discrimination of multiple sclerosis using OCT images from two different centers. Multiple Sclerosis and Related Disorders, 77(September), Article 104846. https://doi.org/10.1016/j.msard.2023.104846
• Diagnostic value of intereye difference metrics for optic neuritis in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders
  
  Oertel, F. C., Zimmermann, H. G., Motamedi, S., Chien, C., Aktas, O., Albrecht, P., Ringelstein, M., Dcunha, A., Pandit, L., Martinez-Lapiscina, E. H., Sanchez-Dalmau, B., Villoslada, P., Palace, J., Roca-Fernández, A., Leite, M. I., Sharma, S. M., Leocani, L., Pisa, M., Radaelli, M., … Petzold, A. (2023). Diagnostic value of intereye difference metrics for optic neuritis in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders. Journal of Neurology, Neurosurgery & Psychiatry, 94(7), 560-566. https://doi.org/10.1136/jnnp-2022-330608
• GMDH-Kalman Filter prediction of high-cycle fatigue life of drilled industrial composites: A hybrid machine learning with limited data
  
  Khayyam, H., Shahkhosravi, N. A., Jamali, A., Naebe, M., Kafieh, R., & Milani, A. S. (2023). GMDH-Kalman Filter prediction of high-cycle fatigue life of drilled industrial composites: A hybrid machine learning with limited data. Expert Systems With Applications, 216, Article 119425. https://doi.org/10.1016/j.eswa.2022.119425
• CNV-Net: Segmentation, Classification and Activity Score Measurement of Choroidal Neovascularization (CNV) Using Optical Coherence Tomography Angiography (OCTA)
  
  Vali, M., Nazari, B., Sadri, S., Pour, E. K., Riazi-Esfahani, H., Faghihi, H., Ebrahimiadib, N., Azizkhani, M., Innes, W., Steel, D. H., Hurlbert, A., Read, J. C., & Kafieh, R. (2023). CNV-Net: Segmentation, Classification and Activity Score Measurement of Choroidal Neovascularization (CNV) Using Optical Coherence Tomography Angiography (OCTA). Diagnostics, 13(7), Article 1309. https://doi.org/10.3390/diagnostics13071309
• Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images with Low-Contrast Sclerochoroidal Junction Using Deep Learning
  
  Arian, R., Mahmoudi, T., Riazi-Esfahani, H., Faghihi, H., Mirshahi, A., Ghassemi, F., Khodabande, A., Kafieh, R., & Khalili Pour, E. (2023). Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images with Low-Contrast Sclerochoroidal Junction Using Deep Learning. Photonics, 10(3), Article 234. https://doi.org/10.3390/photonics10030234
• Dual-Tree Complex Wavelet Input Transform for Cyst Segmentation in OCT Images Based on a Deep Learning Framework
  
  Darooei, R., Nazari, M., Kafieh, R., & Rabbani, H. (2023). Dual-Tree Complex Wavelet Input Transform for Cyst Segmentation in OCT Images Based on a Deep Learning Framework. Photonics, 10(1), Article 11. https://doi.org/10.3390/photonics10010011
• Optimal Deep Learning Architecture for Automated Segmentation of Cysts in OCT Images Using X-Let Transforms
  
  Darooei, R., Nazari, M., Kafieh, R., & Rabbani, H. (2023). Optimal Deep Learning Architecture for Automated Segmentation of Cysts in OCT Images Using X-Let Transforms. Diagnostics, 13(12), Article 1994. https://doi.org/10.3390/diagnostics13121994
• A new convolutional neural network based on combination of circlets and wavelets for macular OCT classification
  
  Arian, R., Vard, A., Kafieh, R., Plonka, G., & Rabbani, H. (2023). A new convolutional neural network based on combination of circlets and wavelets for macular OCT classification. Scientific Reports, 13(1), Article 22582. https://doi.org/10.1038/s41598-023-50164-7
• Differentiation between Pancreatic Ductal Adenocarcinoma and Normal Pancreatic Tissue for Treatment Response Assessment using Multi-Scale Texture Analysis of CT Images
  
  Mahmoudi, T., Radmard, A., Salehnia, A., Ahmadian, A., Davarpanah, A., Kafieh, R., & Arabalibeik, H. (2022). Differentiation between Pancreatic Ductal Adenocarcinoma and Normal Pancreatic Tissue for Treatment Response Assessment using Multi-Scale Texture Analysis of CT Images. Journal of Biomedical Physics and Engineering, 12(6), 655-668. https://doi.org/10.31661/jbpe.v0i0.2102-1283
• Synthetic OCT Data Generation to Enhance the Performance of Diagnostic Models for Neurodegenerative Diseases
  
  Danesh, H., Steel, D. H., Hogg, J., Ashtari, F., Innes, W., Bacardit, J., Hurlbert, A., Read, J. C., & Kafieh, R. (2022). Synthetic OCT Data Generation to Enhance the Performance of Diagnostic Models for Neurodegenerative Diseases. Translational Vision Science & Technology, 11(10), Article 10. https://doi.org/10.1167/tvst.11.10.10
• Glioma segmentation with DWI weighted images, conventional anatomical images, and post-contrast enhancement magnetic resonance imaging images by U-Net
  
  Khorasani, A., Kafieh, R., Saboori, M., & Tavakoli, M. B. (2022). Glioma segmentation with DWI weighted images, conventional anatomical images, and post-contrast enhancement magnetic resonance imaging images by U-Net. Physical and Engineering Sciences in Medicine, 45(3), 925-934. https://doi.org/10.1007/s13246-022-01164-w
• Dynamic Brain Connectivity in Resting-State FMRI Using Spectral ICA and Graph Approach: Application to Healthy Controls and Multiple Sclerosis
  
  Riazi, A. H., Rabbani, H., & Kafieh, R. (2022). Dynamic Brain Connectivity in Resting-State FMRI Using Spectral ICA and Graph Approach: Application to Healthy Controls and Multiple Sclerosis. Diagnostics, 12(9), Article 2263. https://doi.org/10.3390/diagnostics12092263
• Intraretinal Layer Segmentation Using Cascaded Compressed U-Nets
  
  Yadav, S. K., Kafieh, R., Zimmermann, H. G., Kauer-Bonin, J., Nouri-Mahdavi, K., Mohammadzadeh, V., Shi, L., Kadas, E. M., Paul, F., Motamedi, S., & Brandt, A. U. (2022). Intraretinal Layer Segmentation Using Cascaded Compressed U-Nets. JOURNAL OF IMAGING, 8(5), Article 139. https://doi.org/10.3390/jimaging8050139
• Retinal Optical Coherence Tomography in Neuromyelitis Optica (vol 8, e1068, 2021)
  
  Oertel, F. C., Specovius, S., Zimmermann, H. G., Chien, C., Motamedi, S., Bereuter, C., Cook, L., Lana Peixoto, M. A., Fontanelle, M. A., Kim, H. J., Hyun, J., Palace, J., Roca-Fernandez, A., Leite, M. I., Sharma, S., Ashtari, F., Kafieh, R., Dehghani, A., Pourazizi, M., … Paul, F. (2022). Retinal Optical Coherence Tomography in Neuromyelitis Optica (vol 8, e1068, 2021). Neurology: Neuroimmunology & Neuroinflammation, 9(2), Article e1132. https://doi.org/10.1212/nxi.0000000000001132
• Astrocytic outer retinal layer thinning is not a feature in AQP4-IgG seropositive neuromyelitis optica spectrum disorders
  
  Lu, A., Zimmermann, H. G., Specovius, S., Motamedi, S., Chien, C., Bereuter, C., Lana-Peixoto, M. A., Fontenelle, M. A., Ashtari, F., Kafieh, R., Dehghani, A., Pourazizi, M., Pandit, L., D’Cunha, A., Kim, H. J., Hyun, J., Jung, S., Leocani, L., Pisa, M., … Int Clinical Consortium, G. (2022). Astrocytic outer retinal layer thinning is not a feature in AQP4-IgG seropositive neuromyelitis optica spectrum disorders. JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY, 93(2), 188-195. https://doi.org/10.1136/jnnp-2021-327412
• Synthetic OCT data in challenging conditions: three-dimensional OCT and presence of abnormalities
  
  Danesh, H., Maghooli, K., Dehghani, A., & Kafieh, R. (2022). Synthetic OCT data in challenging conditions: three-dimensional OCT and presence of abnormalities. MEDICAL \& BIOLOGICAL ENGINEERING \& COMPUTING, 60(1), 189-203. https://doi.org/10.1007/s11517-021-02469-w
• A Device-independent, Shape Preserving Retinal Optical Coherence Tomography Image Alignment Method Applying TV-Unet for RPE Layer Detection
  
  Saeedizadeh, N., Tajmirriahi, M., Haghani, A., Amini, Z., Pour, E. K., Riazi-Esfahani, H., Fadakar, K., Kafieh, R., & Rabbani, H. (2022). A Device-independent, Shape Preserving Retinal Optical Coherence Tomography Image Alignment Method Applying TV-Unet for RPE Layer Detection. IEEE Transactions on Instrumentation and Measurement, 71. https://doi.org/10.1109/tim.2022.3185653
• Measurement of retinal nerve fiber layer thickness with a deep learning algorithm in ischemic optic neuropathy and optic neuritis
  
  Razaghi, G., Hedayati, E., Hejazi, M., Kafieh, R., Samadi, M., Ritch, R., Subramanian, P. S., & Aghsaei Fard, M. (2022). Measurement of retinal nerve fiber layer thickness with a deep learning algorithm in ischemic optic neuropathy and optic neuritis. Scientific Reports, 12(1), Article 17109. https://doi.org/10.1038/s41598-022-22135-x
• An Interpretable Convolutional Neural Network for P300 Detection: Analysis of Time Frequency Features for Limited Data
  
  Tajmirriahi, M., Amini, Z., Rabbani, H., & Kafieh, R. (2022). An Interpretable Convolutional Neural Network for P300 Detection: Analysis of Time Frequency Features for Limited Data. IEEE SENSORS JOURNAL, 22(9), 8685-8692. https://doi.org/10.1109/jsen.2022.3159475
• Segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and texture descriptors
  
  Mahmoudi, T., Kouzahkanan, Z. M., Radmard, A. R., Kafieh, R., Salehnia, A., Davarpanah, A. H., Arabalibeik, H., & Ahmadian, A. (2022). Segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and texture descriptors. SCIENTIFIC REPORTS, 12(1), Article 3092. https://doi.org/10.1038/s41598-022-07111-9
• A Dual Discriminator Fourier Acquisitive GAN for Generating Retinal Optical Coherence Tomography Images
  
  Tajmirriahi, M., Kafieh, R., Amini, Z., & Lakshminarayanan, V. (2022). A Dual Discriminator Fourier Acquisitive GAN for Generating Retinal Optical Coherence Tomography Images. IEEE Transactions on Instrumentation and Measurement, 71. https://doi.org/10.1109/tim.2022.3189735
• An optimized deep learning approach based on autoencoder network for P300 detection in brain computer interface systems
  
  Afrah, R., Amini, Z., Kafieh, R., & Vard, A. (2022). An optimized deep learning approach based on autoencoder network for P300 detection in brain computer interface systems. Medical Journal of Tabriz University of Medical Sciences, 44(4), 270-280. https://doi.org/10.34172/mj.2022.033
• Retinal Optical Coherence Tomography in Neuromyelitis Optica
  
  Oertel, F. C., Specovius, S., Zimmermann, H. G., Chien, C., Motamedi, S., Bereuter, C., Cook, L., Lana Peixoto, M. A., Fontanelle, M. A., Kim, H. J., Hyun, J., Palace, J., Roca-Fernandez, A., Leite, M. I., Sharma, S., Ashtari, F., Kafieh, R., Dehghani, A., Pourazizi, M., … Paul, F. (2021). Retinal Optical Coherence Tomography in Neuromyelitis Optica. NEUROLOGY-NEUROIMMUNOLOGY \& NEUROINFLAMMATION, 8(6), Article e1068. https://doi.org/10.1212/nxi.0000000000001068
• Absence of astrocytic outer retinal layer thinning in AQP4-IgG seropositive neuromyelitis optica spectrum disorders
  
  Lu, A., Zimmermann, H., Specovius, S., Motamedi, S., Chien, C., Lana-Peixoto, M. A., Fontenelle, M. A., Ashtari, F., Kafieh, R., Pandit, L., Dcunha, A., Kim, H., Hyun, J. W., Leocani, L., Pisa, M., Radaelli, M., Siritho, S., May, E., Tongco, C., … Int Clinical Consortiu, G. (2021). Absence of astrocytic outer retinal layer thinning in AQP4-IgG seropositive neuromyelitis optica spectrum disorders. MULTIPLE SCLEROSIS JOURNAL, 27(2\_SUPPL, 2\_, SI), 493-495.
• Optical Coherence Tomography in Neuromyelitis Optica spectrum disorder and Multiple Sclerosis: A population-based study (vol 47, 102625, 2021)
  
  Ashtari, F., Ataei, A., Kafieh, R., Khodabandeh, Z., Barzegar, M., Raei, M., Dehghani, A., & Mansurian, M. (2021). Optical Coherence Tomography in Neuromyelitis Optica spectrum disorder and Multiple Sclerosis: A population-based study (vol 47, 102625, 2021). MULTIPLE SCLEROSIS AND RELATED DISORDERS, 54, Article 103116. https://doi.org/10.1016/j.msard.2021.103116
• Automated Evaluation of Parapapillary Choroidal Microvasculature in Pseudoexfoliation Syndrome and Pseudoexfoliation Glaucoma
  
  Fard, M. A., Safizadeh, M., Shaabani, A., Kafieh, R., Hojati, S., Afzali, M., Suwan, Y., Ritch, R., & Moghimi, S. (2021). Automated Evaluation of Parapapillary Choroidal Microvasculature in Pseudoexfoliation Syndrome and Pseudoexfoliation Glaucoma. AMERICAN JOURNAL OF OPHTHALMOLOGY, 224, 178-184. https://doi.org/10.1016/j.ajo.2020.12.002
• Retinal OCT Texture Analysis for Differentiating Healthy Controls from Multiple Sclerosis (MS) with/without Optic Neuritis
  
  Tazarjani, H. D., Amini, Z., Kafieh, R., Ashtari, F., & Sadeghi, E. (2021). Retinal OCT Texture Analysis for Differentiating Healthy Controls from Multiple Sclerosis (MS) with/without Optic Neuritis. BIOMED RESEARCH INTERNATIONAL, 2021, Article 5579018. https://doi.org/10.1155/2021/5579018
• A Lightweight Mimic Convolutional Auto-Encoder for Denoising Retinal Optical Coherence Tomography Images
  
  Tajmirriahi, M., Kafieh, R., Amini, Z., & Rabbani, H. (2021). A Lightweight Mimic Convolutional Auto-Encoder for Denoising Retinal Optical Coherence Tomography Images. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 70, Article 4503908. https://doi.org/10.1109/tim.2021.3072109
• Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
  
  Montazerin, M., Sajjadifar, Z., Pour, E. K., Riazi-Esfahani, H., Mahmoudi, T., Rabbani, H., Movahedian, H., Dehghani, A., Akhlaghi, M., & Kafieh, R. (2021). Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images. SCIENTIFIC REPORTS, 11(1), Article 13794. https://doi.org/10.1038/s41598-021-92713-y
• COVID-19 in Iran: Forecasting Pandemic Using Deep Learning
  
  Kafieh, R., Arian, R., Saeedizadeh, N., Amini, Z., Serej, N. D., Minaee, S., Yadav, S. K., Vaezi, A., Rezaei, N., & Javanmard, S. H. (2021). COVID-19 in Iran: Forecasting Pandemic Using Deep Learning. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2021, Article 6927985. https://doi.org/10.1155/2021/6927985
• Evaluation of Asymmetry in Right and Left Eyes of Normal Individuals Using Extracted Features from Optical Coherence Tomography and Fundus Images
  
  Mahmudi, T., Kafieh, R., Rabbani, H., Mehri, A., & Akhlaghi, M. (2021). Evaluation of Asymmetry in Right and Left Eyes of Normal Individuals Using Extracted Features from Optical Coherence Tomography and Fundus Images. JOURNAL OF MEDICAL SIGNALS \& SENSORS, 11(1), 12-23. https://doi.org/10.4103/jmss.jmss%5C_67%5C_19
• Optical Coherence Tomography in Neuromyelitis Optica spectrum disorder and Multiple Sclerosis: A population-based study
  
  Ashtari, F., Ataei, A., Kafieh, R., Khodabandeh, Z., Barzegar, M., Raei, M., Dehghani, A., & Mansurian, M. (2021). Optical Coherence Tomography in Neuromyelitis Optica spectrum disorder and Multiple Sclerosis: A population-based study. MULTIPLE SCLEROSIS AND RELATED DISORDERS, 47, Article 102625. https://doi.org/10.1016/j.msard.2020.102625
• Optical coherence tomography in aquaporin-4-IgG positive neuromyelitis optica spectrum disorders: a collaborative multi-center study
  
  Oertel, F., Specovius, S., Zimmermann, H., Chien, C., Motamedi, S., Cook, L., Lana-Peixoto, M., Fontenelle, M., Kim, H., Hyun, J. W., Palace, J., Roca-Fernandez, A., Ashtari, F., Kafieh, R., Pandit, L., D’Cunha, A., Aktas, O., Ringelstein, M., May, E., … Paul, F. (2020). Optical coherence tomography in aquaporin-4-IgG positive neuromyelitis optica spectrum disorders: a collaborative multi-center study. MULTIPLE SCLEROSIS JOURNAL, 26(3\_SUPPL, 3\_, SI), 33-34.
• Isfahan and Covid-19: Deep spatiotemporal representation
  
  Kafieh, R., Saeedizadeh, N., Arian, R., Amini, Z., Serej, N. D., Vaezi, A., & Javanmard, S. H. (2020). Isfahan and Covid-19: Deep spatiotemporal representation. CHAOS SOLITONS \& FRACTALS, 141, Article 110339. https://doi.org/10.1016/j.chaos.2020.110339
• Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning
  
  Minaee, S., Kafieh, R., Sonka, M., Yazdani, S., & Soufi, G. J. (2020). Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning. MEDICAL IMAGE ANALYSIS, 65, Article 101794. https://doi.org/10.1016/j.media.2020.101794
• Automated Evaluation of Parapapillary Choroidal Microvasculature in Ischemic Optic Neuropathy and Open Angle Glaucoma
  
  Fard, M. A., Salabati, M., Mahmoudzadeh, R., Kafieh, R., Hojati, S., Safizadeh, M., Moghimi, S., Ritch, R., & Subramanian, P. S. (2020). Automated Evaluation of Parapapillary Choroidal Microvasculature in Ischemic Optic Neuropathy and Open Angle Glaucoma. INVESTIGATIVE OPHTHALMOLOGY \& VISUAL SCIENCE, 61(3), Article 35. https://doi.org/10.1167/iovs.61.3.35
• NF-RCNN: Heart localization and right ventricle wall motion abnormality detection in cardiac MRI
  
  Kermani, S., Oghli, M. G., Mohammadzadeh, A., & Kafieh, R. (2020). NF-RCNN: Heart localization and right ventricle wall motion abnormality detection in cardiac MRI. PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 70, 65-74. https://doi.org/10.1016/j.ejmp.2020.01.011
• Automatic Evaluation of Crown Preparation Using Image Processing Techniques: A Substitute to Faculty Scoring in Dental Education
  
  Tahani, B., Rashno, A., Haghighi, H., Monirifard, R., Khomami, H. N., & Kafieh, R. (2020). Automatic Evaluation of Crown Preparation Using Image Processing Techniques: A Substitute to Faculty Scoring in Dental Education. JOURNAL OF MEDICAL SIGNALS \& SENSORS, 10(4), 239-248. https://doi.org/10.4103/jmss.jmss%5C_5%5C_20
• Cohort profile: a collaborative multicentre study of retinal optical coherence tomography in 539 patients with neuromyelitis optica spectrum disorders (CROCTINO)
  
  Specovius, S., Zimmermann, H. G., Oertel, F. C., Chien, C., Bereuter, C., Cook, L. J., Lana Peixoto, M. A., Fontenelle, M. A., Kim, H. J., Hyun, J., Jung, S., Palace, J., Roca-Fernandez, A., Diaz, A. R., Leite, M. I., Sharma, S. M., Ashtari, F., Kafieh, R., Dehghani, A., … Int Clinical Consortium, G. (2020). Cohort profile: a collaborative multicentre study of retinal optical coherence tomography in 539 patients with neuromyelitis optica spectrum disorders (CROCTINO). BMJ OPEN, 10(10), Article e035397. https://doi.org/10.1136/bmjopen-2019-035397
• A MATLAB package for automatic extraction of flow index in OCT-A images by intelligent vessel manipulation
  
  Hojati, S., Kafieh, R., Fardafshari, P., Fard, M. A., & Fouladi, H. (2020). A MATLAB package for automatic extraction of flow index in OCT-A images by intelligent vessel manipulation. SOFTWAREX, 12, Article 100510. https://doi.org/10.1016/j.softx.2020.100510
• An Exact and Fast CBCT Reconstruction via Pseudo-Polar Fourier Transform-Based Discrete Grangeat's Formula
  
  Teyfouri, N., Rabbani, H., Kafieh, R., & Jabbari, I. (2020). An Exact and Fast CBCT Reconstruction via Pseudo-Polar Fourier Transform-Based Discrete Grangeat’s Formula. IEEE Transactions on Image Processing, 29, 5832-5847. https://doi.org/10.1109/tip.2020.2985874
• Automatic production of synthetic labelled OCT images using an active shape model
  
  Danesh, H., Maghooli, K., Dehghani, A., & Kafieh, R. (2020). Automatic production of synthetic labelled OCT images using an active shape model. IET IMAGE PROCESSING, 14(15), 3812-3818. https://doi.org/10.1049/iet-ipr.2020.0075
• Classification of dry age-related macular degeneration and diabetic macular oedema from optical coherence tomography images using dictionary learning
  
  Mousavi, E., Kafieh, R., & Rabbani, H. (2020). Classification of dry age-related macular degeneration and diabetic macular oedema from optical coherence tomography images using dictionary learning. IET IMAGE PROCESSING, 14(8), 1571-1579. https://doi.org/10.1049/iet-ipr.2018.6186
• Forming Optimal Projection Images from Intra-Retinal Layers Using Curvelet-Based Image Fusion Method
  
  Jalili, J., Rabbani, H., Dehnavi, A. M., Kafieh, R., & Akhlaghi, M. (2020). Forming Optimal Projection Images from Intra-Retinal Layers Using Curvelet-Based Image Fusion Method. JOURNAL OF MEDICAL SIGNALS \& SENSORS, 10(2), 76-85. https://doi.org/10.4103/jmss.jmss%5C_43%5C_19
• Local comparison of cup to disc ratio in right and left eyes based on fusion of color fundus images and OCT B-scans
  
  Mokhtari, M., Rabbani, H., Mehri-Dehnavi, A., Kafieh, R., Akhlaghi, M., Pourazizi, M., & Pang, L. (2019). Local comparison of cup to disc ratio in right and left eyes based on fusion of color fundus images and OCT B-scans. INFORMATION FUSION, 51, 30-41. https://doi.org/10.1016/j.inffus.2018.10.010
• An international retrospective multi-center study of retinal optical coherence tomography in neuromyelitis optica spectrum disorders: the CROCTINO study
  
  Oertel, F., Specovius, S., Zimmermann, H., Chien, C., Motamedi, S., Cook, L., Martinez-Lapiscina, E., Lana Peixoto, M., Fontenelle, M., Palace, J., Roca-Fernandez, A., Siritho, S., Altintas, A., Tanriverdi, U., Jacob, A., Huda, S., Marignier, R., Nerrant, E., Calvo, A. C., … Int Clinical Consortium, G. (2019). An international retrospective multi-center study of retinal optical coherence tomography in neuromyelitis optica spectrum disorders: the CROCTINO study. MULTIPLE SCLEROSIS JOURNAL, 25(2, SI), 709-711.
• Automatic Multifaceted Matlab Package for Analysis of Ocular Images (AMPAO)
  
  Kafieh, R., Amini, Z., Rabbani, H., Baghbaderani, B. K., Salafian, B., Mazaheri, F., & Mokhtari, M. (2019). Automatic Multifaceted Matlab Package for Analysis of Ocular Images (AMPAO). SOFTWAREX, 10, Article 100339. https://doi.org/10.1016/j.softx.2019.100339
• Bandlets on Oriented Graphs: Application to Medical Image Enhancement
  
  Kafieh, R., Rabbani, H., & Unal, G. (2019). Bandlets on Oriented Graphs: Application to Medical Image Enhancement. IEEE ACCESS, 7, 32589-32601. https://doi.org/10.1109/access.2019.2903467
• A hybrid graph-based approach for right ventricle segmentation in cardiac MRI by long axis information transition
  
  Oghli, M. G., Mohammadzadeh, A., Kafieh, R., & Kermani, S. (2018). A hybrid graph-based approach for right ventricle segmentation in cardiac MRI by long axis information transition. PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 54, 103-116. https://doi.org/10.1016/j.ejmp.2018.09.011
• Obtaining Thickness Maps of Corneal Layers Using the Optimal Algorithm for Intracorneal Layer Segmentation
  
  Rabbani, H., Kafieh, R., Jahromi, M. K., Jorjandi, S., Dehnavi, A. M., Hajizadeh, F., & Peyman, A. (2016). Obtaining Thickness Maps of Corneal Layers Using the Optimal Algorithm for Intracorneal Layer Segmentation. INTERNATIONAL JOURNAL OF BIOMEDICAL IMAGING, 2016, Article 1420230. https://doi.org/10.1155/2016/1420230
• Three Dimensional Data-Driven Multi Scale Atomic Representation of Optical Coherence Tomography
  
  Kafieh, R., Rabbani, H., & Selesnick, I. (2015). Three Dimensional Data-Driven Multi Scale Atomic Representation of Optical Coherence Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING, 34(5), 1042-1062. https://doi.org/10.1109/tmi.2014.2374354
• Thickness Mapping of Eleven Retinal Layers Segmented Using the Diffusion Maps Method in Normal Eyes
  
  Kafieh, R., Rabbani, H., Hajizadeh, F., Abramoff, M. D., & Sonka, M. (2015). Thickness Mapping of Eleven Retinal Layers Segmented Using the Diffusion Maps Method in Normal Eyes. JOURNAL OF OPHTHALMOLOGY, 2015, Article 259123. https://doi.org/10.1155/2015/259123
• Segmentation of Choroidal Boundary in Enhanced Depth Imaging OCTs Using a Multiresolution Texture Based Modeling in Graph Cuts
  
  Danesh, H., Kafieh, R., Rabbani, H., & Hajizadeh, F. (2014). Segmentation of Choroidal Boundary in Enhanced Depth Imaging OCTs Using a Multiresolution Texture Based Modeling in Graph Cuts. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2014, Article 479268. https://doi.org/10.1155/2014/479268
• Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map
  
  Kafieh, R., Rabbani, H., Abramoff, M. D., & Sonka, M. (2013). Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map. MEDICAL IMAGE ANALYSIS, 17(8), 907-928. https://doi.org/10.1016/j.media.2013.05.006
• An Accurate Multimodal 3-D Vessel Segmentation Method Based on Brightness Variations on OCT Layers and Curvelet Domain Fundus Image Analysis
  
  Kafieh, R., Rabbani, H., Hajizadeh, F., & Ommani, M. (2013). An Accurate Multimodal 3-D Vessel Segmentation Method Based on Brightness Variations on OCT Layers and Curvelet Domain Fundus Image Analysis. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 60(10), 2815-2823. https://doi.org/10.1109/tbme.2013.2263844
• Breast cancer detection from thermal images using bispectral invariant features
  
  EtehadTavakol, M., Chandran, V., Ng, E., & Kafieh, R. (2013). Breast cancer detection from thermal images using bispectral invariant features. INTERNATIONAL JOURNAL OF THERMAL SCIENCES, 69, 21-36. https://doi.org/10.1016/j.ijthermalsci.2013.03.001
• Curvature correction of retinal OCTs using graph-based geometry detection
  
  Kafieh, R., Rabbani, H., Abramoff, M. D., & Sonka, M. (2013). Curvature correction of retinal OCTs using graph-based geometry detection. PHYSICS IN MEDICINE AND BIOLOGY, 58(9), 2925-2938. https://doi.org/10.1088/0031-9155/58/9/2925
• Automatic detection of defects on polyethylene pipe welding using thermal infrared imaging
  
  Kafieh, R., Lotfi, T., & Amirfattahi, R. (2011). Automatic detection of defects on polyethylene pipe welding using thermal infrared imaging. INFRARED PHYSICS \& TECHNOLOGY, 54(4), 317-325. https://doi.org/10.1016/j.infrared.2010.12.010