Honors & Awards

  • Best Paper Award for the 2019-2020 Biennium, CMBBE: Imaging & Visualization Journal (2021)
  • AAPM Expanding Horizons Travel Grant Award, American Association of Physicists in Medicine (2020)
  • AAAI 2020 Student Travel Scholarship, Association for the Advancement of Artificial Intelligence (2020)
  • DeepImaging 2019 Fellowship, LabEx Primes, INSA, Lyon (2019)
  • NVIDIA Best Paper Award, MICCAI Deep Learning in Medical Image Analysis (2018)
  • Graduate Division Fellowship, University of California, Los Angeles (2017-2019)
  • President Gold Medal, Rajshahi University of Engineering & Technology, Bangladesh (2012)

Professional Education

  • BS, Rajshahi University of Engineering & Technology, Computer Science & Engineering (2012)
  • MS, Delaware State University, Computer Science (2016)
  • PhD, University of California, Los Angeles, Computer Science (2020)

Stanford Advisors

Contact

  • Academic
    aimran@stanford.edu
    University - Scholar Department: Radiology Position: Postdoctoral Scholar

Additional Info

  • Mail Code: 5488

Links

Lab Affiliations

All Publications

  • Personalized CT Organ Dose Estimation from Scout Images International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Imran, A., Wang, S., Pal, D., Dutta, S., Patel, B., Zucker, E., Wang, A. 2021

    View details for DOI 10.1007/978-3-030-87202-1_47

  • Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data Journal of Machine Learning for Biomedical Imaging (MELBA) Haque, A., Imran, A., Wang, A., Terzopoulos, D. 2021: 1-25
  • Fast and automatic segmentation of pulmonary lobes from chest CT using a progressive dense V-network COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION Imran, A., Hatamizadeh, A., Ananth, S. P., Ding, X., Tajbakhsh, N., Terzopoulos, D. 2019

    View details for DOI 10.1080/21681163.2019.1672210

    View details for Web of Science ID 000497679900001

  • Noise2Quality: Non-reference, pixel-wise assessment of low dose CT image quality SPIE Medical Imaging: Image Perception, Observer Performance, and Technology Assessment Haque, A., Wang, A., Imran, A. 2022

    View details for DOI 10.1117/12.2611254

  • Personalized CT organ noise estimation from scout images SPIE Medical Imaging: Physics of Medical Imaging Imran, A., Pal, D., Wang, S., Dutta, S., Zucker, E., Wang, A. 2022

    View details for DOI 10.1117/12.2610986

  • Fast Monte Carlo Simulation of Non-Isotropic X-Ray Source for CT Dose Calculation Wang, S., Imran, A., Pal, D., Zucker, E., Wang, A. WILEY. 2021

    View details for Web of Science ID 000673145402029

  • Multi-Adversarial Variational Autoencoder Nets for Simultaneous Image Generation and Classification Deep Learning Applications Imran, A., Terzopoulos, D. Springer Nature Singapore. 2021: 249–271

    View details for DOI https://doi.org/10.1007/978-981-15-6759-9_11

  • Window-Level is a Strong Denoising Surrogate International Workshop on Machine Learning in Medical Imaging (MLMI) Haque, A., Wang, A., Imran, A. 2021

    View details for DOI 10.1007/978-3-030-87589-3_47

  • Upstream Machine Learning in Radiology. Radiologic clinics of North America Sandino, C. M., Cole, E. K., Alkan, C., Chaudhari, A. S., Loening, A. M., Hyun, D., Dahl, J., Imran, A. A., Wang, A. S., Vasanawala, S. S. 2021; 59 (6): 967-985

    Abstract

    Machine learning (ML) and Artificial intelligence (AI) has the potential to dramatically improve radiology practice at multiple stages of the imaging pipeline. Most of the attention has been garnered by applications focused on improving the end of the pipeline: image interpretation. However, this article reviews how AI/ML can be applied to improve upstream components of the imaging pipeline, including exam modality selection, hardware design, exam protocol selection, data acquisition, image reconstruction, and image processing. A breadth of applications and their potential for impact is shown across multiple imaging modalities, including ultrasound, computed tomography, and MRI.

    View details for DOI 10.1016/j.rcl.2021.07.009

    View details for PubMedID 34689881

  • SSIQA: Multi-task learning for non-reference CT image quality assessment with self-supervised noise level prediction 18th International Symposium on Biomedical Imaging (ISBI) Imran, A., Pal, D., Patel, B., Wang, A. IEEE. 2021: 1962–1965

    View details for DOI 10.1109/ISBI48211.2021.9434044

  • MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images 18th International Symposium on Biomedical Imaging (ISBI) Haque, A., Imran, A., Wang, A., Terzopoulos, D. IEEE. 2021

    View details for DOI 10.1109/ISBI48211.2021.9434167

  • Progressive Adversarial Semantic Segmentation 25th International Conference on Pattern Recognition (ICPR) Imran, A., Terzopoulos, D. IEEE. 2021: 4910–4917

    View details for DOI 10.1109/ICPR48806.2021.9412530

  • Fully-Automated Analysis of Scoliosis from Spinal X-Ray Images International Symposium on Computer-Based Medical Systems (CBMS) Imran, A., Huang, C., Tang, H., Fan, W., Cheung, K., To, M., Qian, Z., Terzopoulos, D. IEEE. 2020

    View details for DOI 10.1109/CBMS49503.2020.00029

  • Partly Supervised Multi-Task Learning International Conference on Machine Learning and Applications (ICMLA) Imran, A., Huang, C., Tang, H., Fan, W., Xiao, Y., Hao, D., Qian, Z., Terzopoulos, D. IEEE. 2020: 769–774

    View details for DOI 10.1109/ICMLA51294.2020.00126

  • Self-Supervised, Semi-Supervised, Multi-Context Learning for the Combined Classification and Segmentation of Medical Images (Student Abstract) Imran, A., Huang, C., Tang, H., Fan, W., Xiao, Y., Hao, D., Qian, Z., Terzopoulos, D., Assoc Advancement Artificial Intelligence ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2020: 13815-13816

    View details for Web of Science ID 000668126806100

  • Semi-supervised Multi-task Learning with Chest X-Ray Images Imran, A., Terzopoulos, D., Suk, H. I., Liu, M., Yan, P., Lian, C. SPRINGER INTERNATIONAL PUBLISHING AG. 2019: 151-159

    View details for DOI 10.1007/978-3-030-32692-0_18

    View details for Web of Science ID 000548437800018

  • Multi-adversarial variational autoencoder networks International Conference On Machine Learning And Applications (ICMLA) Imran, A., Terzopoulos, D. IEEE. 2019: 777–782

    View details for DOI 10.1109/ICMLA.2019.00137

  • Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network Imran, A., Hatamizadeh, A., Ananth, S. P., Ding, X., Terzopoulos, D., Tajbakhsh, N., Stoyanov, D., Taylor, Z., Carneiro, G., SyedaMahmood, T. SPRINGER INTERNATIONAL PUBLISHING AG. 2018: 282–90

    View details for DOI 10.1007/978-3-030-00889-5_32

    View details for Web of Science ID 000477761800032

  • Characterization of adipose compartments in mastectomy CT images Imran, A., Bakic, P. R., Pokrajac, D. D., Lo, J. Y., Schmidt, T. G., Chen, G. H. SPIE-INT SOC OPTICAL ENGINEERING. 2018

    View details for DOI 10.1117/12.2293706

    View details for Web of Science ID 000436173700177

  • Optimization of the simulation parameters for improving realism in anthropomorphic breast phantoms Imran, A., Bakic, P. R., Maidment, A. A., Pokrajac, D. D., Flohr, T. G., Lo, J. Y., Schmidt, T. G. SPIE-INT SOC OPTICAL ENGINEERING. 2017

    View details for DOI 10.1117/12.2253903

    View details for Web of Science ID 000405562100178

  • Validation of Cooper's Ligament Thickness in Software Breast Phantoms Kuperavage, A. J., Imran, A., Bakic, P. R., Maidment, A., Pokrajac, D. D., Flohr, T. G., Lo, J. Y., Schmidt, T. G. SPIE-INT SOC OPTICAL ENGINEERING. 2017

    View details for DOI 10.1117/12.2254551

    View details for Web of Science ID 000405562100182

  • Estimation of adipose compartment volumes in CT images of a mastectomy specimen Imran, A., Pokrajac, D. D., Maidment, A. A., Bakic, P. R., Kontos, D., Flohr, T. G., Lo, J. Y. SPIE-INT SOC OPTICAL ENGINEERING. 2016

    View details for DOI 10.1117/12.2217175

    View details for Web of Science ID 000378352900090

  • Spatial Distribution of Adipose Compartments Size, Shape and Orientation in a CT Breast Image of a Mastectomy Specimen Imran, A., Bakic, P. R., Pokrajac, D. D., IEEE IEEE. 2015

    View details for Web of Science ID 000380570400024

  • Monte Carlo Testing and Verification of Numerical Algorithm Implementations Pokrajac, D. D., Imran, A., Bakic, P. R., IEEE IEEE. 2015: 56-59

    View details for Web of Science ID 000380406700010