2026 Hamid R. Tizhoosh: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	52	5004	4867	2326	2247	280	14083

Overview

Hamid R. Tizhoosh is a researcher affiliated with the Mayo Clinic in the United States. Their work broadly spans the fields of Computer Science and Medicine, with a particular focus on applications of Artificial Intelligence in medical imaging and diagnostics.

The main fields of study for Tizhoosh include:

Computer Science
Medicine

Within these fields, their research often concentrates on the following subfields:

Artificial Intelligence
Computer Vision and Pattern Recognition
Radiology, Nuclear Medicine and Imaging
Oncology
Molecular Biology

Key research topics covered throughout their publications include:

AI in cancer detection
Radiomics and Machine Learning in Medical Imaging
Digital Imaging for Blood Diseases
Image Retrieval and Classification Techniques
Colorectal Cancer Screening and Detection
COVID-19 diagnosis using AI
Cell Image Analysis Techniques

Tizhoosh has contributed to numerous scientific articles published across multiple journals and venues. Frequent publication venues include:

arXiv (Cornell University)
Scientific Reports
Research Square (Research Square)
Lecture Notes in Computer Science
American Journal Of Pathology

Several recently published papers highlight the scope of their research work, including:

Federated learning and differential privacy for medical image analysis, 2022, Scientific Reports
Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides, 2021, Medical Image Analysis
Yottixel - An Image Search Engine for Large Archives of Histopathology Whole Slide Images, 2020, Medical Image Analysis
Decentralized federated learning through proxy model sharing, 2023, Nature Communications
Automated bone marrow cytology using deep learning to generate a histogram of cell types, 2022, Communications Medicine

Throughout their career, Tizhoosh has frequently collaborated with a group of co-authors, including:

Morteza Babaie
Shivam Kalra
Clinton J.V. Campbell
Taher Dehkharghanian
Shahryar Rahnamayan

Best Publications

Opposition-Based Learning: A New Scheme for Machine Intelligence

H.R. Tizhoosh

2350
Citations
Opposition-Based Differential Evolution

S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

1995
Citations
Artificial intelligence and digital pathology: Challenges and opportunities

Hamid Reza Tizhoosh;Liron Pantanowitz

535
Citations
Quasi-oppositional Differential Evolution

S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

460
Citations
A novel population initialization method for accelerating evolutionary algorithms

Shahryar Rahnamayan;Hamid R. Tizhoosh;Magdy M. A. Salama

450
Citations
Opposition versus randomness in soft computing techniques

Shahryar Rahnamayan;Hamid R. Tizhoosh;Magdy M. A. Salama

416
Citations
Image thresholding using type II fuzzy sets

Hamid R. Tizhoosh

387
Citations
Federated learning and differential privacy for medical image analysis

Unknown

382
Citations
Opposition-Based Reinforcement Learning

Hamid R. Tizhoosh

246
Citations
Opposition-Based Differential Evolution Algorithms

S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

236
Citations
Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides.

Abtin Riasatian;Morteza Babaie;Danial Maleki;Shivam Kalra

201
Citations
Convolutional neural networks for histopathology image classification: Training vs. Using pre-trained networks

Brady Kieffer;Morteza Babaie;Shivam Kalra;H. R. Tizhoosh

169
Citations
Opposition-Based Differential Evolution for Optimization of Noisy Problems

S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

152
Citations
Improving the Convergence of Backpropagation by Opposite Transfer Functions

M. Ventresca;H.R. Tizhoosh

142
Citations
Ignorance functions. An application to the calculation of the threshold in prostate ultrasound images

H. Bustince;M. Pagola;E. Barrenechea;J. Fernandez

138
Citations
Decentralized federated learning through proxy model sharing

Unknown

134
Citations
Fuzzy image processing

Horst Haußecker;Hamid R. Tizhoosh

130
Citations
Yottixel - An Image Search Engine for Large Archives of Histopathology Whole Slide Images.

Shivam Kalra;Hamid R. Tizhoosh;Charles Choi;Sultaan Shah

128
Citations
Fast fuzzy edge detection

H.R. Tizhoosh

118
Citations
IRIS Segmentation: Detecting Pupil, Limbus and Eyelids

E.M. Arvacheh;H.R. Tizhoosh

118
Citations
Filter fusion for image enhancement using reinforcement learning

F. Sahba;H.R. Tizhoosh

115
Citations
A sequential search-space shrinking using CNN transfer learning and a Radon projection pool for medical image retrieval

Amin Khatami;Morteza Babaie;Morteza Babaie;HR Tizhoosh;Abbas Khosravi

112
Citations
Medical Image Classification via SVM Using LBP Features from Saliency-Based Folded Data

Zehra Camlica;H.R. Tizhoosh;Farzad Khalvati

102
Citations

Frequent Co-Authors

Shahryar Rahnamayan University of Ontario Institute of Technology

Magdy M. A. Salama University of Waterloo

Fakhri Karray Mohamed bin Zayed University of Artificial Intelligence

Mohamed S. Kamel University of Waterloo

Saeid Nahavandi Swinburne University of Technology

Abbas Khosravi Deakin University

Ali Ghodsi University of Waterloo

Andrew K. C. Wong University of Waterloo

Aaron Fenster University of Western Ontario

Graham W. Taylor University of Guelph

External Links

Personal website of Hamid R. Tizhoosh Google Scholar page

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