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Selected Publications

Peer-Reviewed Articles

Akerman, M.A., Choudhary, S., Liebmann, J.M., Cioffi, G.A., Chen, R.W.S., Thakoor, K.A. "Extracting decision-making features from the unstructured eye movements of clinicians on glaucoma OCT reports and developing AI models to classify expertise." Frontiers in Medicine - Ophthalmology, 2023. [pdf]

Thakoor, K.A., Yao, J., Bordbar, D., Moussa, O., Lin, W., Sajda, P., Chen, R. “A Multimodal Deep Learning System to Distinguish Late Stages of AMD and to Compare Expert vs. AI Ocular Biomarkers.” Scientific Reports, 12(1), p.1‑11, 2022.

Thakoor, K.A., Li, X., Tsamis, E., Zemborain, Z.Z., De Moraes, C.G., Sajda, P., Hood, D.C. “Strategies to improve convolutional neural network generalizability and reference standards for glaucoma detection from OCT scans.” Translational Vision Science and Technology, 10(4), pp.16‑16, 2021.

Koorathota, S., Thakoor, K., Hong, L., Mao, Y., Adelman, P., Sajda, P. “A Recurrent Neural Network for Attenuating Non‑cognitive Components of Pupil Dynamics.” Frontiers in Psychology, 12, p.12, 2021.

Thakoor, K., Koorathota, S., Hood, D., Sajda, P. “Robust and Interpretable Convolutional Neural Networks to Detect Glaucoma in Optical Coherence Tomography Images.” IEEE Transactions on Biomedical Engineering, 68(8), pp. 2456‑2466, August 2021. Early Access: https://ieeexplore.ieee.org/document/9286420, 8 December 2020.

Tsamis, E., Bommakanti, N., Sun, A., Thakoor, K., De Moraes, C.G., and Hood, D.C. “An Automated Method for Assessing Topographical Structure‑Function Agreement in Abnormal Glaucomatous Regions.” Translational Vision Science and Technology, 9(4), 2020.

Thakoor, K., Andrews, J., Hauksson, E. and Heaton, T. “From Earthquake Source Parameters to Ground Motion Warnings near You: The ShakeAlert Earthquake Information to Ground‑Motion (eqInfo2GM) Method.” Seismological Research Letters, 90(3), pp.1243‑1257, 2019.

Thakoor, K.A., “Cognitive Mechanisms Underlying the Classification of Reduced Dimensionality, Information Rich Image Representations.” IEEE Intelligent Systems, 31(2), pp.9‑20, 2016.

Thakoor K., Mante, N., Zhang, C. et al. “A System for Assisting the Visually Impaired in Localization and Grasp of Desired Objects.” Springer International Publishing, Switzerland; L. Agapito, et al. (Eds): Lecture Notes in Computer Science (LNCS), ECCV 2014 Workshops, Part III, Volume 8927, pp. 643‑657, 2015.

Conference Papers

Tian, Y., Zang, M., Sharma, A., Gu, S., Leshno, A., Thakoor, K.A. “Glaucoma Progression Detection and Humphrey Visual Field Prediction Using Discriminative and Generative Vision Transformers.” OMIA-X Workshop in conjunction with MICCAI 2023, October 2023.

Kaushal, S., Sun, Y., Zukerman, R., Chen, R.W.S., Thakoor, K. “Detecting Eye Disease Using Vision Transformers Informed by Ophthalmology Resident Gaze Data.” IEEE Engineering in Medicine and Biology Society (EMBC), 24-27 July 2023.

Tian, Y., Wu, G., Bearelly, S., Laine, A., Thakoor, K.*, Shehnav, L.* “DVT-Net: A Multimodal Deep Vascular Topology Network for Disease Prediction.” International Symposium Biomedical Imaging (ISBI), 2023 (*co-senior author/equal advising).

Thakoor, K., Carter, A., Song, G., Wax, A., Moussa O., Chen, R.W.S., Hendon, C., Sajda, P., “Enhancing Portable OCT Image Quality via GANs for AI-Based Eye Disease Detection.” Medical Image Computing and Computer Assisted Intervention (MICCAI) aFfordable healthcare and AI for Resource diverse global health (FAIR), Singapore, 18-22 September, 2022. Best Paper Award.

Thakoor, K., Koorathota, S., Hood, D., Sajda, P. “Robust and Interpretable Convolutional Neural Networks to Detect Glaucoma in Optical Coherence Tomography Images.” IEEE International Conference on Image Processing (ICIP), 2021.

Thakoor, K., Bordbar, D., Yao, J., Moussa, O., Chen, R., Sajda, P. “Hybrid 3D‑2D Deep Learning for Detection of Neovascular Age‑Related Macular Degeneration Using Optical Coherence Tomography B‑Scans and Angiography Volumes.” International Symposium on Biomedical Imaging (ISBI), 2021.

Koorathota, S., Thakoor, K., Adelman, P., Mao, Y., Liu, X., Sajda, P. “Sequence Models in Eye Tracking: Predicting Pupil Diameter During Learning.” In ACM Symposium on Eye Tracking Research and Applications, pp. 1‑3, 2020.

Thakoor, K.A., Li, X., Tsamis, E., Sajda, P. and Hood, D.C. “Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks.” In 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2036‑2040, 2019.

Drori, I., Dwivedi, I., Shrestha, P., Wan, J., Wang, Y., He, Y., Mazza, A., Krogh‑Freeman, H., Leggas, D., Sandridge, K., Nan, L., Thakoor, K., Josh, C., Goenka, S., Chen, K., Pe’er, I. “High quality prediction of protein Q8 secondary structure by diverse neural network architectures.” Neural Information Processing 2018 Workshop on Machine Learning for Molecules and Materials, 8 December 2018.

Thakoor, K.A., “Classification of Biological Images and Natural Scenes via Reduced Dimensionality, Information Rich Representations.” In Proceedings of the 28th International Conference on Computer Applications in Industry and Engineering, pp. 12‑14, San Diego, CA, USA, 2015.

Thakoor, K.A., “Neural Basis for Enhanced Classification Accuracy of Reduced Dimensionality, Information Rich Representations of Images.” In Proceedings of the 37th International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Italy, Aug. 25‑29, 2015.

Thakoor, K.A., “Reduced Dimensionality, Information Rich Visual Representations for Scene Classification.” In 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), pp. 43‑48, 2015, 2nd Place Best Student Paper Award.

Thakoor K.A., Marat, S., Nasiatka, P.J., et al. “Attention Biased Speeded Up Robust Features (AB‑SURF): A Neurally‑Inspired Object Recognition Algorithm for A Wearable Aid for the Visually‑Impaired.” In 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), pp. 1‑6, 2013, Best Student Paper Award.

Peer-Reviewed Abstracts

Sharma, A., Tian, Y., Kaushal, S., Zukerman, R., Chen, R.W.S., Liebmann, J.M., Cioffi, G.A., Thakoor, K.A. “A Foundational CNN Model for Predicting Eye Fixations on OCT Reports.” ARVO Annual Meeting, 2023.

Salas, J., Zukerman, R., Moussa, O., Gu, S., Leshno, A., Liebmann, J.M., Cioffi, G.A., Thakoor, K.A. “Impact of AI on Retrospective Glaucoma Diagnosis.” ARVO Annual Meeting, 2023.

Thakoor, K., Leshno, A., La Bruna, S., Tsamis, E., De Moraes, C.G., Sajda, P., Harizman, N., Liebmann, J., Cioffi, G.A., Hood, D.C. “Evaluation of a Deep Learning Model on a Real‑World Clinical Glaucoma Dataset.” ARVO Annual Meeting, 2022.

Thakoor, K., Bordbar, D., Yao, J., Moussa, O., Lin, W., Scherbakova, I., Diaconita, V., Sajda, P., Chen, R. “A Hybrid Deep Learning System to Distinguish Late Stages of AMD and to Compare Expert vs. Machine AMD Risk Features.” Investigative Ophthalmology and Visual Science, 62(8), pp.2146‑2146, 2021.

Li, X., Tsamis, E., Thakoor, K.A., Zemborain, Z., De Moraes, C.G., Hood, D.C. “Evaluating the Transferability of Deep Learning Models that Distinguish Glaucomatous from Healthy OCT Circumpapillary Disc Scans.” Investigative Ophthalmology and Visual Science, 61(7), pp.4548‑4548, 2020.

Thakoor, K., Tsamis, E., De Moraes, C.G., Sajda, P., Hood, D.C. “Impact of Reference Standard, Data Augmentation, and OCT Input on Glaucoma Detection Accuracy by CNNs on a New Test Set.” Investigative Ophthalmology and Visual Science, 61(7), pp.4540‑4540, 2020.

Tsamis, E., Bommakanti, N., Sun, A., Thakoor, K., De Moraes, C.G., and Hood, D.C. “An automated method for assessing topographical structure‑function agreement in abnormal regions in glaucoma.” Investigative Ophthalmology and Visual Science, 60(9), pp.6141‑6141, 2019.

Thakoor, K.A., Zheng, Q., Nan, L., Li, X., Tsamis, E.M., Rajshekhar, R., Dwivedi, I., Drori, I., Sajda, P. and Hood, D.C., “Assessing the Ability of Convolutional Neural Networks to Detect Glaucoma from OCT Probability Maps.” Investigative Ophthalmology and Visual Science, 60(9), pp.1464‑1464, 2019.

Adebiyi A., et al. (4th co‑author of 4). “Feedback measures for a wearable visual aid designed for the visually impaired.” Investigative Ophthalmology and Visual Science, 54 (15), pp. 2764‑276, 2013.

LeMieux, M., Barman, S., Mark, R., Opatkiewicz, J., Thakoor, K.A., Bao, Z., “Nanotube Network Transistors on Functional Surfaces.” Materials Research Society Symposium P: Carbon Nanotubes and Related Low‑Dimensional Materials, 60(9), 24‑28 March, 2008.

Rajan, S.K., Thakoor, K.A., Yang, T.J., Gao, F., “VEGF Levels Aid Prediction of Chemotherapy Induced Myeloid Toxicity and Presence of Extranodal Disease in Diffuse Large B‑Cell Lymphoma (DLBCL).” Blood, 106: 11 (2), A4725, November, 2005.