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N. (Navchetan) Awasthi

Faculty of Science
Informatics Institute
Visiting address
  • Science Park 904
Postal address
  • Postbus 94323
    1090 GH Amsterdam
Contact details
  • Publications

    2024

    • Gupta, U., Paluru, N., Nankani, D., Kulkarni, K., & Awasthi, N. (2024). A comprehensive review on efficient artificial intelligence models for classification of abnormal cardiac rhythms using electrocardiograms. Heliyon, 10(5), Article e26787. https://doi.org/10.1016/j.heliyon.2024.e26787

    2023

    • Awasthi, N., van Anrooij, L., Jansen, G., Schwab, H. M., Pluim, J. P. W., & Lopata, R. G. P. (2023). Bandwidth Improvement in Ultrasound Image Reconstruction Using Deep Learning Techniques. Healthcare (Switzerland), 11(1), Article 123. https://doi.org/10.3390/healthcare11010123 [details]

    2022

    • Awasthi, N., Vermeer, L., Fixsen, L. S., Lopata, R. G. P., & Pluim, J. P. W. (2022). LVNet: Lightweight Model for Left Ventricle Segmentation for Short Axis Views in Echocardiographic Imaging. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 69(6), 2115-2128. https://doi.org/10.1109/TUFFC.2022.3169684 [details]

    2021

    • Awasthi, N., Dayal, A., Cenkeramaddi, L. R., & Yalavarthy, P. K. (2021). Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 68(6), 2023-2037. Article 9383274. https://doi.org/10.1109/TUFFC.2021.3068190
    • Awasthi, N., Gupta, S., Kiran, A., & Pardasani, R. (2021). State-of-the-art equipment for rapid and accurate diagnosis of COVID-19. In V. E. Balas, O. German, G. Wang, M. Arif, & O. A. Postolache (Eds.), Biomedical Engineering Tools for Management for Patients with COVID-19 (pp. 19-40). Academic Press. https://doi.org/10.1016/B978-0-12-824473-9.00012-4
    • Awasthi, N., Kalva, S. K., Pramanik, M., & Yalavarthy, P. K. (2021). Dimensionality reduced plug and play priors for improving photoacoustic tomographic imaging with limited noisy data. Biomedical optics express, 12(3), 1320-1338. https://doi.org/10.1364/BOE.415182
    • Awasthi, N., Pardasani, R., & Gupta, S. (2021). Multi-threshold Attention U-Net (MTAU) Based Model for Multimodal Brain Tumor Segmentation in MRI Scans. In A. Crimi, & S. Bakas (Eds.), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 6th International Workshop, BrainLes 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers (pp. 168-178). (Lecture Notes in Computer Science; Vol. 12659). Springer. https://doi.org/10.1007/978-3-030-72087-2_15
    • Jansen, G., Awasthi, N., Schwab, H. M., & Lopata, R. (2021). Enhanced Radon Domain Beamforming Using Deep-Learning-Based Plane Wave Compounding. In 2021 IEEE International Ultrasonics Symposium (IUS) IEEE Computer Society. https://doi.org/10.1109/IUS52206.2021.9593731
    • Katare, P., Awasthi, N., Venukumar, A., & Gorthi, S. S. (2021). Low-Cost, Continuous Motion Imaging, Computationally Augmented Whole Slide Imager for Digital Pathology. IEEE Journal of Selected Topics in Quantum Electronics, 27(4), Article 9384204. https://doi.org/10.1109/JSTQE.2021.3067389
    • Kulkarni, K., Awasthi, N., Roberts, J. D., & Armoundas, A. A. (2021). Utility of a Smartphone-Based System (cvrPhone) in Estimating Minute Ventilation from Electrocardiographic Signals. Telemedicine and e-Health, 27(12), 1433-1439. https://doi.org/10.1089/tmj.2020.0507
    • Wu, M., Awasthi, N., Rad, N. M., Pluim, J. P. W., & Lopata, R. G. P. (2021). Advanced ultrasound and photoacoustic imaging in cardiology. Sensors, 21(23), Article 7947. https://doi.org/10.3390/s21237947

    2020

    • Awasthi, N., Jain, G., Kalva, S. K., Pramanik, M., & Yalavarthy, P. K. (2020). Deep Neural Network-Based Sinogram Super-Resolution and Bandwidth Enhancement for Limited-Data Photoacoustic Tomography. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 67(12), 2660-2673. Article 9018129. https://doi.org/10.1109/TUFFC.2020.2977210
    • Awasthi, N., Katare, P., Gorthi, S. S., & Yalavarthy, P. K. (2020). Guided filter based image enhancement for focal error compensation in low cost automated histopathology microscopic system. Journal of Biophotonics, 13(11), Article e202000123. https://doi.org/10.1002/jbio.202000123
    • Pardasani, R., & Awasthi, N. (2020). Classification of 12 Lead ECG Signal Using 1D-Convolutional Neural Network with Class Dependent Threshold. In 2020 Computing in Cardiology (CinC 2020): Rimini, Italy, 13-16 September 2020 (pp. 321-324). (Computing in Cardiology; Vol. 47). IEEE. https://doi.org/10.22489/CinC.2020.277
    • Pardasani, R., Chaudhuri, R., Awasthi, N., & Goel, M. (2020). Machine Learning and Deep Learning Approaches to Quantify Respiratory Distress Severity and Predict Critical Alarms. In 2020 IEEE International Conference on Healthcare Informatics, ICHI 2020 Article 9374301 (2020 IEEE International Conference on Healthcare Informatics, ICHI 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICHI48887.2020.9374301
    • Pardasani, R., Chaudhuri, R., Awasthi, N., Chaurasia, S., & Maya, S. (2020). Quantitative Assessment of Respiratory Distress Using Convolutional Neural Network for Multivariate Time Series Segmentation. In 2020 Computing in Cardiology (CinC 2020): Rimini, Italy, 13-16 September 2020 (pp. 465-468). (Computing in Cardiology; Vol. 47). IEEE. https://doi.org/10.22489/CinC.2020.271

    2019

    • Awasthi, N., Prabhakar, K. R., Kalva, S. K., Pramanik, M., Babu, R. V., & Yalavarthy, P. K. (2019). PA-Fuse: Deep supervised approach for the fusion of photoacoustic images with distinct reconstruction characteristics. Biomedical optics express, 10(5), 2227-2243. Article #357458. https://doi.org/10.1364/BOE.10.002227

    2018

    • Awasthi, N., Kalva, S. K., Pramanik, M., & Yalavarthy, P. K. (2018). Image-guided filtering for improving photoacoustic tomographic image reconstruction. Journal of Biomedical Optics, 23(9), Article 091413. https://doi.org/10.1117/1.JBO.23.9.091413
    • Awasthi, N., Kalva, S. K., Pramanik, M., & Yalavarthy, P. K. (2018). Vector extrapolation methods for accelerating iterative reconstruction methods in limited-data photoacoustic tomography. Journal of Biomedical Optics, 23(7), Article 071204. https://doi.org/10.1117/1.JBO.23.7.071204
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