Staff profile

Please check out my personal webpage for more information.

Rahele Kafieh is an Assistant Professor in Bioengineering at Durham University and serves as an EPSRC Women in Engineering Ambassador. Her research primarily focuses on harnessing Artificial Intelligence (AI) for biomedical image and signal processing, in close collaboration with clinicians and the NHS. With a career spanning over 13 years in health-related projects and AI-driven medical data analysis, she possesses a wealth of expertise in tasks such as anatomical feature localization in medical images, medical data classification for disease diagnosis, and numerical feature extraction from medical signals and images using sophisticated deep learning models. Her contributions to the field are evidenced by over 120 research articles she has authored.

 Rahele has demonstrated her ability to secure substantial funding for her projects, including notable grants such as the EPSRC IAA, UKRI MRC Ageing Research Development Award, Switzerland research seed money, Einstein Forum grant, National Institute for Medical Research Development grant, and TÜBİTAK grant. Her work has received widespread recognition, with one of her articles on AI applications in the COVID population earning the Article of the Year Award from the Computational and Mathematical Methods in Medicine journal. Furthermore, another paper published in the Medical Image Analysis Journal, boasting over 700 citations, was honored with the Best Paper Award in the COVID domain by the Ministry of Health in Iran.

 In addition to her impressive accolades, Rahele is currently leading the EPSRC IAA project titled "Enhancing Healthcare with AI-Based Home Monitoring for Retinal Diseases," conducted in collaboration with Siloton Limited. This project addresses Age-related Macular Degeneration (AMD), a prevalent cause of vision impairment in the UK. The project's objective is to develop AI-driven software supporting home-based Optical Coherence Tomography (OCT) devices to enable early detection and treatment of AMD, thereby preserving vision.

 One of her flagship projects, funded by the UKRI MRC award with a budget of 400k, is titled "OCTage: monitoring the ageing brain via Optical Coherence Tomography of the eyes" (MR/Y010825/1). This initiative in close collaboration with Newcastle University, aims to establish a non-invasive measure of general brain health in aging individuals by analysing OCT images of the retina. The project endeavours to bridge the gap between chronological age and retinal age to develop an AI-assisted tool for screening neurodegenerative diseases, particularly Parkinson's, utilizing images sourced from high-street optometrists. Additionally, the project is committed to addressing barriers to clinical impact and proposing innovative solutions to overcome them.

Honors and Awards

• PSRC Women in Engineering Ambassador
•  Top Ten Abstract Award for abstract titled "Autoencoder-Based Feature Extraction for Discrimination of Multiple Sclerosis Using Thickness Maps of Retinal Layers" in Collaborative Community on Ophthalmic Imaging (CCOI), 2023.
• Article of the Year Award for ‘COVID-19 in Iran: Forecasting Pandemic Using Deep Learning,’ in Computational and Mathematical Methods in Medicine, 2021.
• Best Paper Award in Covid-domain for ‘Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning’ in Medical image analysis, Ministry of Health, Iran, 2021.
• Best Young USERN Office Award, 2017.
• Voluntary Contribution Award (Student Travel) by IEEE R8 VCF, 2014.
• Best Researcher Award, Isfahan University of Medical Sciences, 2013.
• Ranked First in National PhD Entrance Exam in Biomedical Engineering, Iran, 2013.
• Best Paper Award from ISCEE07, Isfahan, Iran, 2007.

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

• 2024: External Examiner for Jamie Pordoy’s PhD at University of West London (UWL):
• 2023: Invited talk in International Webinar on Image Analysis in Ophthalmology by Appraise :
• 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 DEMON Network: Artificial Intelligence in Eye imaging: An easy-to-use mirror of brain-related abnormalities in Dementia
• 2022: Topic editor: in Artificial Intelligence in Cancer Diagnosis and Therapy:
• 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: 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: 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

• Hajizadeh, F., Kafieh, R., & Tajmirriahi, M. (2023). Introduction to Optical Coherence Tomography. In F. Hajizadeh (Ed.), Atlas of Ocular Optical Coherence Tomography (1-34). (2). Springer Verlag. https://doi.org/10.1007/978-3-031-07410-3_1
• 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 (3-1 - 3-23). IOP Publishing. https://doi.org/10.1088/978-0-7503-2056-6ch3

Conference Paper

• 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.), . https://doi.org/10.1117/12.2594152
• Jorjandi, S., Rabbani, H., Amini, Z., & Kafieh, R. (2019). OCT Image Denoising Based on 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.
• 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.
• 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.
• 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.), . https://doi.org/10.1117/12.2044046
• Kafieh, R., Rabbani, H., & Gazor, S. (2014). Combination of Graph Theoretic Grouping and Time-Frequency Analysis for Image Segmentation.
• Kafieh, R., Rabbani, H., Abramoff, M., & Sonka, M. (2013). INTRA-RETINAL LAYER SEGMENTATION OF OPTICAL COHERENCE TOMOGRAPHY USING DIFFUSION MAP.
• 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.
• 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.), . https://doi.org/10.1117/12.2026520
• Kafieh, R., Rabbani, H., Abramoff, M. D., & Sonka, M. (2012). OCT Image Alignment Using Diffusion Maps. In D. Haynor, & S. Ourselin (Eds.), . https://doi.org/10.1117/12.912259
• 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.), . https://doi.org/10.1117/12.911065
• Kafieh, R., & Rabbani, H. (2011). WAVELET-BASED MEDICAL INFRARED IMAGE NOISE REDUCTION USING LOCAL MODEL FOR SIGNAL AND NOISE.
• 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.),
• Kafieh, R., mehri, A., & sadri, S. (2007). Automatic landmark detection in-cephalometry using a modified active shape model with sub image matching.
• Kafieh, R., Sadri, S., mehri, A., & Raji, H. (2007). Using a combination of model based and intelligent methods in automatic landmark detection in cephalometry.
• Kafieh, R., Mehri, A., & Amirfattahi, R. (2007). Detection of ventricular arrhythmias using roots location in AR-modelling.

Edited book

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

Journal Article

• 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
• Suwan, Y., Aghsaei Fard, M., Vilainerun, N., Petpiroon, P., Tantraworasin, A., Teekhasaenee, C., …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
• 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
• Parsarad, S., Saeedizadeh, N., Soufi, G. J., Shafieyoon, S., Hekmatnia, F., Zarei, A. P., …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
• Vali, M., Mohammadi, M., Zarei, N., Samadi, M., Atapour-Abarghouei, A., Supakontanasan, W., …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
• Khodabandeh, Z., Rabbani, H., Ashtari, F., Zimmermann, H. G., Motamedi, S., Brandt, A. U., …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
• Oertel, F. C., Zimmermann, H. G., Motamedi, S., Chien, C., Aktas, O., Albrecht, P., …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 and Psychiatry, 94(7), 560-566. https://doi.org/10.1136/jnnp-2022-330608
• 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
• Vali, M., Nazari, B., Sadri, S., Pour, E. K., Riazi-Esfahani, H., Faghihi, H., …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
• Arian, R., Mahmoudi, T., Riazi-Esfahani, H., Faghihi, H., Mirshahi, A., Ghassemi, F., …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
• 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
• 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
• 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
• 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
• Danesh, H., Steel, D. H., Hogg, J., Ashtari, F., Innes, W., Bacardit, J., …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
• 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
• 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
• Yadav, S. K., Kafieh, R., Zimmermann, H. G., Kauer-Bonin, J., Nouri-Mahdavi, K., Mohammadzadeh, V., …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
• Oertel, F. C., Specovius, S., Zimmermann, H. G., Chien, C., Motamedi, S., Bereuter, C., …Paul, F. (2022). Retinal Optical Coherence Tomography in Neuromyelitis Optica (vol 8, e1068, 2021). https://doi.org/10.1212/nxi.0000000000001132
• Lu, A., Zimmermann, H. G., Specovius, S., Motamedi, S., Chien, C., Bereuter, C., …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
• 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
• 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
• Razaghi, G., Hedayati, E., Hejazi, M., Kafieh, R., Samadi, M., Ritch, R., …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
• Mahmoudi, T., Kouzahkanan, Z. M., Radmard, A. R., Kafieh, R., Salehnia, A., Davarpanah, A. 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
• 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 Science, 44(4), 270-280. https://doi.org/10.34172/mj.2022.033
• Saeedizadeh, N., Tajmirriahi, M., Haghani, A., Amini, Z., Pour, E. K., Riazi-Esfahani, H., …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
• Danesh, H., Maghooli, K., Dehghani, A., & Kafieh, R. (2022). Synthetic OCT data in challenging conditions: three-dimensional OCT and presence of abnormalities. https://doi.org/10.1007/s11517-021-02469-w
• Oertel, F. C., Specovius, S., Zimmermann, H. G., Chien, C., Motamedi, S., Bereuter, C., …Paul, F. (2021). Retinal Optical Coherence Tomography in Neuromyelitis Optica. https://doi.org/10.1212/nxi.0000000000001068
• Lu, A., Zimmermann, H., Specovius, S., Motamedi, S., Chien, C., Lana-Peixoto, M. A., …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
• Ashtari, F., Ataei, A., Kafieh, R., Khodabandeh, Z., Barzegar, M., Raei, M., …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
• Fard, M. A., Safizadeh, M., Shaabani, A., Kafieh, R., Hojati, S., Afzali, M., …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
• 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
• 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 and Sensors, 11(1), 12-23. https://doi.org/10.4103/jmss.jmss%5C_67%5C_19
• Ashtari, F., Ataei, A., Kafieh, R., Khodabandeh, Z., Barzegar, M., Raei, M., …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
• 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
• Montazerin, M., Sajjadifar, Z., Pour, E. K., Riazi-Esfahani, H., Mahmoudi, T., Rabbani, H., …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
• Kafieh, R., Arian, R., Saeedizadeh, N., Amini, Z., Serej, N. D., Minaee, S., …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
• Kafieh, R., Saeedizadeh, N., Arian, R., Amini, Z., Serej, N. D., Vaezi, A., & Javanmard, S. H. (2020). Isfahan and Covid-19: Deep spatiotemporal representation. https://doi.org/10.1016/j.chaos.2020.110339
• Oertel, F., Specovius, S., Zimmermann, H., Chien, C., Motamedi, S., Cook, L., …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
• 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
• Fard, M. A., Salabati, M., Mahmoudzadeh, R., Kafieh, R., Hojati, S., Safizadeh, M., …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
• Kermani, S., Oghli, M. G., Mohammadzadeh, A., & Kafieh, R. (2020). NF-RCNN: Heart localization and right ventricle wall motion abnormality detection in cardiac MRI. https://doi.org/10.1016/j.ejmp.2020.01.011
• 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
• 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
• 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 and Sensors, 10(2), 76-85. https://doi.org/10.4103/jmss.jmss%5C_43%5C_19
• 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 and Sensors, 10(4), 239-248. https://doi.org/10.4103/jmss.jmss%5C_5%5C_20
• Specovius, S., Zimmermann, H. G., Oertel, F. C., Chien, C., Bereuter, C., Cook, L. J., …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
• 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
• 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
• 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
• Oertel, F., Specovius, S., Zimmermann, H., Chien, C., Motamedi, S., Cook, L., …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
• 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
• 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
• 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. https://doi.org/10.1016/j.ejmp.2018.09.011
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• Kafieh, R., Rabbani, H., Abramoff, M. D., & Sonka, M. (2013). Curvature correction of retinal OCTs using graph-based geometry detection. https://doi.org/10.1088/0031-9155/58/9/2925
• Kafieh, R., Lotfi, T., & Amirfattahi, R. (2011). Automatic detection of defects on polyethylene pipe welding using thermal infrared imaging. https://doi.org/10.1016/j.infrared.2010.12.010