Abdullah-Al-Zubaer Imran
Email: aimran [AT] Stanford [DOT] edu

I am a Postdoctoral Research Scholar in the Wang group in the Radiological Sciences Laboratory (RSL) at Stanford University. I work with Professor Adam Wang and Professor Evan Zucker on upstream AI for improved medical imaging.

Prior to Postdoc, I obtained my PhD in Computer Science from the University of California, Los Angeles (UCLA) Graphics and Vision Laboratory in 2020, advised by Distinguished Professor Demetri Terzopoulos. My PhD research was focused on effective deep learning, with a particular focus in semi-supervised learning and multitask learning, applied to computer vision and medical imaging.

I also received an MS in Computer Science degree from Delaware State University (DSU) in 2016 and a Bachelor in Computer Science and Engineering (CSE) degree from the Rajshahi University of Engineering and Technology (RUET), Bangladesh in 2012.

During my MS at the DSU Medical Imaging and Simulation (MEDIS) Laboratory, in collaboration with the Penn XPL Lab, I worked on an NIH-funded breast cancer research project, jointly advised by Professor David Pokrajac and Professor Predrag Bakic. I have also spent time at Philips Corporate Research NA at Cambridge, MA and Tencent Medical AI Lab at Palo Alto, CA.

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Updates

  • Oct 2021: Review article on Upstream Machine Learning published in RCNA [article]
  • Sep 2021: Presented our CT organ dose prediction paper at MICCAI 2021
  • Aug 2021: Paper accepted at MLMI 2021 [preprint]
  • Jul 2021: Abstract accepted at RSNA 2021 as an oral paper
  • May 2021: Manuscript accepted at MELBA!
  • May 2021: Paper (early) accepted at MICCAI 2021! (Top 13%)
  • Apr 2021: Our article won the CMBBE: Imaging & Visualization Best Paper Award for the 2019-20 biennium!
  • Apr 2021: Presented our SSIQA (oral) and MultiMix (poster) papers at ISBI 2021
  • Feb 2021: Received the Stanford Bio-X Travel award!
  • Feb 2021: Gave a guest lecture to the Advanced Data Mining class at Utah State University
  • Jan 2021: Two papers accepted at ISBI 2021!
Research

My research is primarily centered around artificial intelligence, computer vision, and medical imaging. I am particularly interested in developing advanced AI-powered medical imaging tools for clinical applications. Recently, I focus on semi-supervised learning with multi-task learning, self-supervised learning, and generative modeling. I am also interested in visual representation learning and domain generalization for medical image analysis tasks.

Theses

From Fully-Supervised, Single-Task to Scarcely-Supervised, Multi-Task Deep Learning for Medical Image Analysis
PhD Thesis 2020 at the University of California, Los Angeles, California, USA
[Abstract]  [Oral]  [BibTex]
Estimation of Breast Anatomical Descriptors From Mastectomy CT Images
MS Thesis 2016 at Delaware State University, Dover, Delaware, USA
[Abstract]  [Oral]  [BibTex]
Automatic Extraction of Road Networks From High Resolution Satellite Images
BS Thesis 2012 at the Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh
[Abstract]  [Oral]  [BibTex]
Selected Publications

Personalized CT Organ Dose Estimation from Scout Images
Abdullah-Al-Zubaer Imran, Sen Wang, Debashish Pal, Sandeep Dutta, Bhavik Patel, Evan Zucker, Adam Wang
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2021
[Paper]  [Slides]  [Poster]  [BibTex]
Window-Level is a Strong Denoising Surrogate
Ayaan Haque, Adam Wang, Abdullah-Al-Zubaer Imran,
MICCAI Machine Learning in Medical Imaging (MLMI) 2021
[Paper]  [Project]  [Slides]  [Code]  [BibTex]
SSIQA: Multi-Task Learning for Non-Reference CT Image Quality Assessment With Self-Supervised Noise Level Prediction
Abdullah-Al-Zubaer Imran, Debashish Pal, Bhavik Patel, Adam Wang
IEEE International Symposium on Biomedical Imaging (ISBI) 2021
[Paper]  [Oral]  [BibTex]
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images
Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang, Demetri Terzopoulos
IEEE International Symposium on Biomedical Imaging (ISBI) 2021
[Preprint]  [Paper]  [Poster]  [BibTex]  [Code]
Multi-Adversarial Variational Autoencoder Nets for Simultaneous Image Generation and Classification
Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
Deep Learning Applications, Volume 2, 2021
[Chapter]  [BibTex]
Partly Supervised Multi-task Learning
Abdullah-Al-Zubaer Imran, Chao Hunag, Hui Tang, Wei Fan, Yuan Xiao, Dingjun Hao, Zhen Qian, Demetri Terzopoulos
International Conference on Machine Learning and Applications (ICMLA) 2020
[Paper]  [BibTex]  [Oral]
Progressive Adversarial Semantic Segmentation
Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
International Conference on Pattern Recognition (ICPR) 2020
[Preprint]  [BibTex]  [Oral]  [Poster]
Fully-Automated Analysis of Scoliosis from Spinal X-Ray Images
Abdullah-Al-Zubaer Imran, Chao Hunag, Hui Tang, Wei Fan, Kenneth MC Cheung, Michael To, Zhen Qian, Demetri Terzopoulos
IEEE 33rd International Symposium on Computer Based Medical Systems (CBMS) 2020
[Paper]  [BibTex]  [Oral]  [Video]
Self-supervised Semi-Supervised Multi-Context Learning for the Combined Classification and Segmentation of Medical Images
Abdullah-Al-Zubaer Imran, Chao Hunag, Hui Tang, Wei Fan, Yuan Xiao, Dingjun Hao, Zhen Qian, Demetri Terzopoulos
AAAI Conference on Artificial Intelligence 2020
[Paper]  [BibTex]  [Poster]
Bipartite Distance for Shape-Aware Landmark Detection in Spinal X-Ray Images
Abdullah-Al-Zubaer Imran, Chao Hunag, Hui Tang, Wei Fan, Kenneth MC Cheung, Michael To, Zhen Qian, Demetri Terzopoulos
Medical Imaging Meets NeurIPS (Med-NeruIPS) 2019
[Paper]  [BibTex]  [Poster]
Fast and Automatic Segmentation of Pulmonary Lobes From Chest CT Using a Progressive Dense V-Network
Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Nima Tajbakhsh, Demetri Terzopoulos
Computer Methods in Biomechanics & Biomedical Engineering: Imaging & Visualization 2019
[Paper]  [BibTex
Semi-Supervised Multi-Task Learning With Chest X-Ray Images
Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
MICCAI Machine Learning in Medical Imaging (MLMI) 2019
[Paper]  [BibTex]  [Poster]  [Code]
Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network
Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Nima Tajbakhsh, Demetri Terzopoulos
MICCAI Deep Learning in Medical Image Analysis (DLMIA) 2018
[Paper]  [BibTex]  [Oral
Reviewing

  • IEEE Access
  • Patterns - Cell Press
  • Knowledge-Based Systems
  • Machine Learning for Health (ML4H)
  • Deep Learning for Computer Vision (DLCV)
  • IEEE Transactions on Medical Imaging (TMI)
  • IEEE International Symposium on Biomedical Imaging (ISBI)
  • International Conference on Learning Representations (ICLR)
  • Medical Image Computing & Computed Assisted Intervention (MICCAI)
  • International Conference on Advances in Electronics Engineering (ICAEE)
Teaching

Teaching Assistant of CS, UCLA Samueli School of Engineering

Spring 2020 Winter 2020 Spring 2019 Winter 2019 Fall 2018
Lecturer of ECE, North South University (NSU)

Summer 2017 Spring 2017
Lecturer of CSE, Ahsanullah University of Science & Technology (AUST)

Summer 2014
    Fall 2013
      Lecturer of CSE, Northern University Bangladesh (NUB)

      Fall 2012
        Spring 2013
          Summer 2013
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