Pranjal Sahu
Email: psahu@cs.stonybrook.edu

I am a PhD candidate in Computer Science working under Dr. Hong Qin at Stony Brook University. My research focus is on Deep Learning applications in the field of Biomedical Imaging. Some of the problems which I work on include image classification, projection de-noising, volume reconstruction etc. I did my summer internship at Siemens Healthineers, Malvern in 2019 and 2020 where I worked on pathological lung volume segmentation from CT scans.

I did my Bachelors (Hons) in Computer Science from IIT Kharagpur in 2013 and later gained experience in software development working in startups for 3 years. I was fortunate to take Computer Vision and Computer Graphics courses under Dr. Rajiv Ranjan Sahay and Dr. Jayanta Mukhopadhyay at IIT Kharagpur which motivated me to pursue PhD in this field. I am active on Twitter where I regularly share interesting blog posts and resources related to Deep Learning, Computer Vision, Computer Graphics and Optimization.

I am looking for postdoc openings in academia or research positions in the industry related to Medical Imaging, Computer Vision, Machine Learning.

CV | Google Scholar | Github | Twitter | LinkedIn | ResearchGate

Journal Publications
sym

[NEW] Structure Correction for Robust Volume Segmentation in Presence of Tumors
Pranjal Sahu, Yiyuan Zhao, Parmeet Bhatia, Luca Bogoni, Anna Jerebko, and Hong Qin

abstract | pdf | bibtex
IEEE Journal of Biomedical and Health Informatics, J-BHI
, 2020
Impact Factor: 5.180

@article{9122557,
  author={P. {Sahu} and Y. {Zhao} and P. {Bhatia} 
  and L. {Bogoni} and A. {Jerebko} and H. {Qin}},
  journal={IEEE Journal of Biomedical and Health Informatics}, 
  title={Structure Correction for Robust Volume 
  Segmentation in Presence of Tumors}, 
  year={2020},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/JBHI.2020.3004296}}
sym

A Lightweight Multi-section CNN for Lung Nodule Classification and Malignancy Estimation
Pranjal Sahu, Dantong Yu, Mallesham Dasari, Fei Hou and Hong Qin

abstract | pdf | bibtex
IEEE Journal of Biomedical and Health Informatics, J-BHI
, 2018
Impact Factor: 5.180

@article{sahu2018lightweight,
  title={A lightweight multi-section CNN for lung nodule 
  classification and malignancy estimation},
  author={Sahu, Pranjal and Yu, Dantong and Dasari, 
  Mallesham and Hou, Fei and Qin, Hong},
  journal={IEEE journal of biomedical and health informatics},
  volume={23},
  number={3},
  pages={960--968},
  year={2018},
  publisher={IEEE}
}
Conference Publications
sym

[NEW] Streaming 360-Degree Videos Using Super-Resolution
Mallesham Dasari, Arani Bhattacharya, Santiago Vargas, Pranjal Sahu, et al.

abstract | pdf | bibtex
INFOCOM, 2020

@inproceedings{duan2020scatter,
  title={Scatter correction with deep learning
  approach for contrast enhanced digital
  breast tomosynthesis (CEDBT) in both
  cranio-caudal (CC) view and mediolateral oblique (MLO) view},
  author={Duan, Xiaoyu and Sahu, Pranjal and
  Huang, Hailiang and Zhao, Wei},
  booktitle={15th International Workshop
  on Breast Imaging (IWBI2020)},
  volume={11513},
  pages={115130Q},
  year={2020},
  organization={International Society
  for Optics and Photonics}
}
sym

[NEW] Scatter correction with deep learning approach for contrast enhanced digital breast tomosynthesis (CEDBT) in both cranio-caudal (CC) view and mediolateral oblique (MLO) view
Xiaoyu Duan, Pranjal Sahu, Hailiang Huang, Wei Zhao

abstract | pdf | bibtex
IWBI, 2020 (Oral)

@inproceedings{duan2020scatter,
  title={Scatter correction with deep learning
  approach for contrast enhanced digital
  breast tomosynthesis (CEDBT) in both
  cranio-caudal (CC) view and mediolateral oblique (MLO) view},
  author={Duan, Xiaoyu and Sahu, Pranjal and
  Huang, Hailiang and Zhao, Wei},
  booktitle={15th International Workshop
  on Breast Imaging (IWBI2020)},
  volume={11513},
  pages={115130Q},
  year={2020},
  organization={International Society
  for Optics and Photonics}
}
sym

Using virtual digital breast tomosynthesis for de-noising of low-dose projection images
Pranjal Sahu, Hailiang Huang, Wei Zhao and Hong Qin

abstract | pdf | bibtex
IEEE International Symposium on Biomedical Imaging, ISBI, 2019

@inproceedings{sahu2019using,
  title={Using Virtual Digital Breast Tomosynthesis 
  for De-Noising of Low-Dose Projection Images},
  author={Sahu, Pranjal and Huang, Hailiang and 
  Zhao, Wei and Qin, Hong},
  booktitle={2019 IEEE 16th International Symposium on 
  Biomedical Imaging (ISBI 2019)},
  pages={1647--1651},
  year={2019},
  organization={IEEE}
}
sym

Apply lightweight deep learning on internet of things for low-cost and easy-to-access skin cancer detection
Pranjal Sahu, Dantong Yu, Hong Qin

abstract | pdf | bibtex
Medical Imaging, SPIE, 2018 (Best Demo Award)

  @inproceedings{sahu2018apply,
  title={Apply lightweight deep learning 
  on internet 
  of things for low-cost and 
  easy-to-access 
  skin cancer detection},
  author={Sahu, Pranjal and Yu, 
  Dantong and Qin, Hong},
  booktitle={Medical Imaging 2018: 
  Imaging Informatics 
  for Healthcare, Research, and Applications},
  volume={10579},
  pages={1057912},
  year={2018},
  organization={International Society 
  for Optics and Photonics}
}
sym

In-Operando Tracking and Prediction of Transition in Material System using LSTM
Pranjal Sahu, Dantong Yu, Kevin Yager, Mallesham Dasari and Hong Qin

abstract | pdf | bibtex
Autonomous Infrastructure for Science, HPDC, 2018

@inproceedings{sahu2018operando,
  title={In-Operando Tracking and Prediction of 
  Transition in Material System using LSTM},
  author={Sahu, Pranjal and Yu, Dantong and 
  Yager, Kevin and Dasari, Mallesham 
  and Qin, Hong},
  booktitle={Proceedings of the 1st 
  International 
  Workshop on Autonomous 
  Infrastructure for Science},
  pages={6},
  year={2018},
  organization={ACM}
}
sym

SHREC'17 Track: Protein Shape Retrieval
Na Song, Daniela Craciun and others

abstract | pdf | bibtex
Eurographics Workshop on 3D Object Retrieval, 2017

@inproceedings{Song2017SHREC17TP,
  title={SHREC’17 Track: Protein Shape Retrieval},
  author={Na Song and Daniela Craciun and 
  Charles Christoffer and Xusi Han and 
  Daisuke Kihara and Guillaume Levieux 
  and Matthieu Montes and Hong Qin and 
  Pranjal Sahu and Genki Terashi and 
  Haiguang Liu},
  year={2017}
}
Teaching
pacman

CSE 328: Fundamentals of Computer Graphics
Instructor: Dr. Hong Qin

CSE 377: Medical Imaging
Instructor: Dr. Allen Tannenbaum

Awards and Talks
  • Invited to give talk at Bell labs, Murray Hill on Deep Learning applications in Medical Imaging (2019)
  • Computer Science Chairman Fellowship (2016-2017)
  • Best Demo Award in SPIE Medical Imaging, Houston (2018)
  • Represented (C.G.) state in National Children Science Congress, Guwahati (2005)