Giorgos Hadjigeorghiou
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Interests
Giorgos Hadjigeorghiou has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Adam Shephard
Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK
1 shared publication - David Epstein
University of Warwick
1 shared publication - Fayyaz Minhas
University of Warwick
1 shared publication - Johnathan Pocock
Department of Computer Science, University of Warwick, Coventry, U.K.
1 shared publication - Mohsin Bilal
Information Systems Department, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
1 shared publication - Mostafa Jahanifar
University of Warwick
1 shared publication
Latest Publications
- Open Access
TIAToolbox: An End-to-End Toolbox for Advanced Tissue Image Analytics
Computational Pathology (CPath) has seen rapid growth in recent years, driven by advanced deep learning (DL) algorithms. These algorithms typically share the same sequence of steps. However, due to the sheer size and complexity of handling large multi-gigapixel whole-slide images, there is no open-source software library that provides a generic end-to-end API for pathology image analysis using best practices for CPath. Most researchers have designed custom pipelines from the bottom-up, restricting the development of advanced CPath algorithms to specialist users. To help overcome this bottleneck, we present TIAToolbox, a Python toolbox designed to make CPath more accessible to new and advanced CPath scientists and pathologists alike. We provide a usable and adaptable library with efficient, cutting-edge and unit-tested tools for data loading, pre-processing, model inference, post-processing and visualization. This enables all kinds of users to easily build upon recent DL developments in the CPath literature. TIAToolbox provides a user-friendly modular API to enable seamless integration of advanced DL algorithms. We show with the help of examples how state-of-the-art DL algorithms can be streamlined using TIAToolbox.
Open AccessTIAToolbox: An End-to-End Toolbox for Advanced Tissue Image Analytics
Computational Pathology (CPath) has seen rapid growth in recent years, driven by advanced deep learning (DL) algorithms. These algorithms typically share the same sequence of steps. However, due to the sheer size and complexity of handling large multi-gigapixel whole-slide images, there is no open-source software library that provides a generic end-to-end API for pathology image analysis using best practices for CPath. Most researchers have designed custom pipelines from the bottom-up, restricting the development of advanced CPath algorithms to specialist users. To help overcome this bottleneck, we present TIAToolbox, a Python toolbox designed to make CPath more accessible to new and advanced CPath scientists and pathologists alike. We provide a usable and adaptable library with efficient, cutting-edge and unit-tested tools for data loading, pre-processing, model inference, post-processing and visualization. This enables all kinds of users to easily build upon recent DL developments in the CPath literature. TIAToolbox provides a user-friendly modular API to enable seamless integration of advanced DL algorithms. We show with the help of examples how state-of-the-art DL algorithms can be streamlined using TIAToolbox.