PUBLICATIONS

 

Peer Reviewed Articles

Zang, M., Mukund, P., Forsyth, B., Laine, A. F., & Thakoor, K. A. "Predicting Clinician Fixations on Glaucoma OCT Reports via CNN-Based Saliency Prediction Methods." IEEE Open Journal of Engineering in Medicine and Biology. 2024. [pdf]

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.111, 2022.

[pdf]

 

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.1616, 2021.

[pdf]

 

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

[pdf]

 

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. 24562466, August 2021. Early Access: https://ieeexplore.ieee.org/document/9286420, 8 December 2020.

[pdf]

 

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

 [pdf]


Thakoor, K., Andrews, J., Hauksson, E. and Heaton, T. “From Earthquake Source Parameters to Ground Motion Warnings near You: The ShakeAlert Earthquake Information to GroundMotion (eqInfo2GM) Method.” Seismological Research Letters, 90(3), pp.12431257, 2019.

 [pdf]


Thakoor, K.A., “Cognitive Mechanisms Underlying the Classification of Reduced Dimensionality, Information Rich Image Representations.” IEEE Intelligent Systems, 31(2), pp.920, 2016.

 [pdf]


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. 643657, 2015.

 [pdf]

Conference Papers


Lau, W.T., Tian, Y., Kenia, R., Aima, S., Thakoor, K.A. "Using Expert Gaze for Self-Supervised and Supervised Contrastive Learning of Glaucoma from OCT Data." Conference on Health, Inference, and Learning (CHIL), June 2024.


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.

 [pdf]


Thakoor, K., Bordbar, D., Yao, J., Moussa, O., Chen, R., Sajda, P. “Hybrid 3D2D Deep Learning for Detection of Neovascular AgeRelated Macular Degeneration Using Optical Coherence Tomography BScans and Angiography Volumes.” International Symposium on Biomedical Imaging (ISBI), 2021.

 [pdf]


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. 13, 2020.

 [pdf]


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. 20362040, 2019.

 [pdf]


Drori, I., Dwivedi, I., Shrestha, P., Wan, J., Wang, Y., He, Y., Mazza, A., KroghFreeman, 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. 

 [pdf]


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. 1214, 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. 2529, 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. 4348, 2015, 2nd Place Best Student Paper Award.


Thakoor K.A., Marat, S., Nasiatka, P.J., et al. “Attention Biased Speeded Up Robust Features (ABSURF): A NeurallyInspired Object Recognition Algorithm for A Wearable Aid for the VisuallyImpaired.” In 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), pp. 16, 2013, Best Student Paper Award.

[pdf]

Peer-reviewed Abstracts


Choudhary, S., Cui, A., Favila, S., Talsania, S., Yeager, L., Rosenberg, S., Thakoor, K.A., "Machine Learning Approach to Detect Subtle Differences between 

Normal and Amblyopic Eye Movements in Children." ARVO Annual Meeting, 2024.

Tian, Y., Zang, M., Gu, S.Z., Leshno, A., Emmanouil, T., Thakoor, K.A., "Long-term Visual Field Appearance Prediction Using Generative Vision Transformers for Ophthalmic Education and Patient Follow-up", ARVO Annual Meeting, 2024.

Walker, S., Tian, Y., Semiller, E., Winterbottom, M., Thakoor, K.A., "Characterizing Task Performance Via Eye Tracking", ARVO Annual Meeting, 2024.


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 RealWorld Clinical Glaucoma Dataset.” ARVO Annual Meeting, 2022.

 [pdf]


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.21462146, 2021.

 [pdf]


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.45484548, 2020.

 [pdf]


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.45404540, 2020.


Tsamis, E., Bommakanti, N., Sun, A., Thakoor, K., De Moraes, C.G., and Hood, D.C. “An automated method for assessing topographical structurefunction agreement in abnormal regions in glaucoma.” Investigative Ophthalmology and Visual Science, 60(9), pp.61416141, 2019.

 [pdf]


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.14641464, 2019.


Adebiyi A., et al. (4th coauthor of 4). “Feedback measures for a wearable visual aid designed for the visually impaired..” Investigative Ophthalmology and Visual Science, 54 (15), pp. 2764276, 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 LowDimensional Materials, 60(9), 2428 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 BCell Lymphoma (DLBCL).” Blood, 106: 11 (2), A4725, November, 2005.

[pdf]