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Talha Qaiser

I am a PhD student of Prof Nasir Rajpoot at the Tissue Image Analytics Lab, Department of Computer Science, University of Warwick.

My interest involves developing robust applications for computer-assisted grading of cancer by using deep learning and statistical machine learning algorithms.

Education

July, 2015 - present, PhD in Computer Science
Department of Computer Science, The University of Warwick, UK
Research: A Pilot Software System for Computer-Assisted Grading of Breast Cancer

2007-2011 BS in Computer Engineering
Deartment of Electrical Engineering, COMSATS Institute of Information Technology, Pakistan
Reserach: A Computer Vision Based Wheelchair for Handicaps
Secured Campus and Institute Silver Medals

Projects

  1. HER2 Scoring Contest for Breast Histology Images
  2. An Integrated Environment for Tissue Morphometrics
  3. Persistent Homology for Fast Tumor Segemtation in Whole Slide Images
  4. Automated Immunohistochemical Scoring of HER2 cases
  5. Tumor Segmentation in Breast Metastasis Histology Images
  6. Mitotic Cell Count in Tumor Rich Breast Histology Images

Employment

  1. Research Assitant at Qatar University (Nov 2014 - May 2015)
  2. Computer Vision Developer (Full time freelancer) at Upwork & co-founder at AAMSONS Technologies (Nov 2012 - Oct 2014)

Publications

  1. Qaiser, Talha, and Nasir Rajpoot. "Learning where to see next: Attention model for automated immunohistochemical scoring." (2018).
  2. Graham, Simon, Muhammad Shaban, Talha Qaiser, Syed Ali Khurram, and Nasir Rajpoot. "Classification of lung cancer histology images using patch-level summary statistics." In Medical Imaging 2018: Digital Pathology, vol. 10581, p. 1058119. International Society for Optics and Photonics, 2018.
  3. Qaiser, Talha, Abhik Mukherjee, Chaitanya Reddy Pb, Sai D. Munugoti, Vamsi Tallam, Tomi Pitkäaho, Taina Lehtimäki et al. "HER 2 challenge contest: a detailed assessment of automated HER 2 scoring algorithms in whole slide images of breast cancer tissues." Histopathology 72, no. 2 (2018): 227-238.
  4. Bejnordi, Babak Ehteshami, Mitko Veta, Paul Johannes van Diest, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen AWM van der Laak ...., Talha Qaiser, ...., et al. "Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer." Jama 318, no. 22 (2017): 2199-2210.
  5. Xue, Mingzhan, Alaa Shafie, Talha Qaiser, Nasir M. Rajpoot, Gregory Kaltsas, Sean James, Kishore Gopalakrishnan et al. "Glyoxalase 1 copy number variation in patients with well differentiated gastro-entero-pancreatic neuroendocrine tumours (GEP-NET)." Oncotarget 8, no. 44 (2017): 76961.
  6. Qaiser, Talha, Yee-Wah Tsang, David Epstein, and Nasir Rajpoot. "Tumor Segmentation in Whole Slide Images Using Persistent Homology and Deep Convolutional Features." In Annual Conference on Medical Image Understanding and Analysis, pp. 320-329. Springer, Cham, 2017.
  7. Hamidinekoo, Azam, Zobia Suhail, Talha Qaiser, and Reyer Zwiggelaar. "Investigating the Effect of Various Augmentations on the Input Data Fed to a Convolutional Neural Network for the Task of Mammographic Mass Classification." In Annual Conference on Medical Image Understanding and Analysis, pp. 398-409. Springer, Cham, 2017.
  8. Qaiser, Talha, Korsuk Sirinukunwattana, Kazuaki Nakane, Yee-Wah Tsang, David Epstein, and Nasir Rajpoot. "Persistent Homology for Fast Tumor Segmentation in Whole Slide Histology Images." Procedia Computer Science 90 (2016): 119-124. [link] best_paper_award
  9. Qaiser, Talha, K. Sirinukunwattana, and N. Rajpoot. "An Integrated Environment For Tissue Morphometrics And Analytics." Diagnostic Pathology 1, no. 8 (2016). [link]

Academic Awards and Experiences

  • Fully Funded Studentship: For Postgraduate Studies by University Hospitals Coventry and Warwickshire.
  • Won Best Paper Award: At the 20th Medical Image Understanding and Analysis Conference.
  • Silver Medalist: Awarded Campus and Institute Silver Medals in BS Computer Engineering.
  • Azure Research: Co-Investigator on Azure-Warwick Pilot Study on Pathology Image Analytics in the Cloud.
  • Organized the “Her2 Scoring Contest” for breast histology Images at the “Pathology Society of Great Britain and Ireland” in 2016.
  • Invited talks at the MIUA-2017, MIUA-2016, ECDP-2016, BBACGR-2015.
  • Organized the “Intel Workshop-Accelerate Your Code” that brings interactive training for researchers and programmers with an appetite to make their code run faster.
  • Developed an interactive framework for tissue morphometrics that could assist the pathologist to perform analytics and produce more accurate means to assess cancer.
  • Program committee member for IJCAI-ECAI-2018 and MICCAI-COMPAY-2018.

BitBucket

For more details about private BitBucket repositories.
Contact: t.qaiser@warwick.ac.uk

Profile Picture

Talha Qaiser

PhD Student, Tissue Image Analytics Lab, Department of Computer Science, University of Warwick

t dot qaiser at warwick dot ac dot uk

LinkedIn linkedin
GitHub github

Google Scholar googleScholar

ResearchGate RG

Upwork upwork