no code implementations • 26 Aug 2023 • Benyamin Ghojogh, Morteza Babaie
We enumerate various examples for philomatics and psychomatics, some of which are explained in more depth.
1 code implementation • 25 Jul 2023 • Kimia Hemmatirad, Morteza Babaie, Jeffrey Hodgin, Liron Pantanowitz, H. R. Tizhoosh
Conclusions: Automated glomeruli detection in human kidney images is possible using modern AI models.
no code implementations • 24 Apr 2023 • Abubakr Shafique, Morteza Babaie, Ricardo Gonzalez, H. R. Tizhoosh
In this work, we are proposing a targeted image search approach, inspired by the pathologists workflow, which may use information from multiple IHC biomarker images when available.
no code implementations • 24 Apr 2023 • Abubakr Shafique, Morteza Babaie, Ricardo Gonzalez, Adrian Batten, Soma Sikdar, H. R. Tizhoosh
In the first step, IHC biomarker images are aligned with the H&E images using one coordinate system and orientation.
no code implementations • 29 Aug 2022 • Sobhan Hemati, Shivam Kalra, Morteza Babaie, H. R. Tizhoosh
Learning suitable Whole slide images (WSIs) representations for efficient retrieval systems is a non-trivial task.
no code implementations • 29 Jul 2021 • Abubakr Shafique, Morteza Babaie, Mahjabin Sajadi, Adrian Batten, Soma Skdar, H. R. Tizhoosh
The registration was performed automatically by first detecting landmarks in both images, using the scale-invariant image transform (SIFT), followed by the fast sample consensus (FSC) protocol for finding point correspondences and finally aligned the images.
no code implementations • 15 Feb 2021 • Sobhan Shafiei, Morteza Babaie, Shivam Kalra, H. R. Tizhoosh
The Kimia Path24 dataset has been introduced as a classification and retrieval dataset for digital pathology.
no code implementations • 29 Oct 2020 • Danial Maleki, Mehdi Afshari, Morteza Babaie, H. R. Tizhoosh
The quality of the images can be negatively affected when the glass slides are ink-marked by pathologists to delineate regions of interest.
no code implementations • 8 Aug 2020 • Aditya Sriram, Shivam Kalra, Morteza Babaie, Brady Kieffer, Waddah Al Drobi, Shahryar Rahnamayan, Hany Kashani, Hamid. R. Tizhoosh
In this paper, we propose a novel image descriptor called Forming Local Intersections of Projections (FLIP) and its multi-resolution version (mFLIP) for representing histopathology images.
no code implementations • 30 Jul 2020 • Morteza Babaie, Hany Kashani, Meghana D. Kumar, Hamid. R. Tizhoosh
Content-based image retrieval (CBIR) is an essential part of computer vision research, especially in medical expert systems.
no code implementations • 7 May 2020 • Manit Zaveri, Shivam Kalra, Morteza Babaie, Sultaan Shah, Savvas Damskinos, Hany Kashani, H. R. Tizhoosh
In this paper, we extract deep features of the images available on TCGA dataset with known magnification to train a classifier for magnification recognition.
no code implementations • 20 Nov 2019 • Shivam Kalra, H. R. Tizhoosh, Sultaan Shah, Charles Choi, Savvas Damaskinos, Amir Safarpoor, Sobhan Shafiei, Morteza Babaie, Phedias Diamandis, Clinton JV Campbell, Liron Pantanowitz
The emergence of digital pathology has opened new horizons for histopathology and cytology.
no code implementations • 15 Sep 2019 • H. R. Tizhoosh, Shivam Kalra, Shalev Lifshitz, Morteza Babaie
In recent years, artificial neural networks have achieved tremendous success for many vision-based tasks.
no code implementations • 17 Mar 2019 • Morteza Babaie, H. R. Tizhoosh
Whole slide imaging (WSI) refers to the digitization of a tissue specimen which enables pathologists to explore high-resolution images on a monitor rather than through a microscope.
no code implementations • 17 Mar 2019 • Wafa Chenni, Habib Herbi, Morteza Babaie, H. R. Tizhoosh
The main contribution of this work is representing a WSI by selecting a small number of patches for algorithmic processing (e. g., indexing and search).
no code implementations • 30 Apr 2018 • Meghana Dinesh Kumar, Morteza Babaie, Hamid Tizhoosh
We investigate the concept of deep barcodes and propose two methods to generate them in order to expedite the process of classification and retrieval of histopathology images.
no code implementations • 11 Oct 2017 • Morteza Babaie, H. R. Tizhoosh, Amin Khatami, M. E. Shiri
This paper attempts to show that the dense sampling to generate the histogram of local Radon projections has a much higher discrimination capability than the global one.
no code implementations • 11 Oct 2017 • Brady Kieffer, Morteza Babaie, Shivam Kalra, H. R. Tizhoosh
We explore the problem of classification within a medical image data-set based on a feature vector extracted from the deepest layer of pre-trained Convolution Neural Networks.
no code implementations • 27 Sep 2017 • Meghana Dinesh Kumar, Morteza Babaie, Shujin Zhu, Shivam Kalra, H. R. Tizhoosh
This paper is a comparative study describing the potential of using local binary patterns (LBP), deep features and the bag-of-visual words (BoVW) scheme for the classification of histopathological images.
no code implementations • 22 May 2017 • Morteza Babaie, Shivam Kalra, Aditya Sriram, Christopher Mitcheltree, Shujin Zhu, Amin Khatami, Shahryar Rahnamayan, H. R. Tizhoosh
In this paper, we introduce a new dataset, \textbf{Kimia Path24}, for image classification and retrieval in digital pathology.
no code implementations • 2 Jan 2017 • Morteza Babaie, H. R. Tizhoosh, Shujin Zhu, M. E. Shiri
Our method (Single Projection Radon Barcode, or SP-RBC) uses only a few Radon single projections for each image as global features that can serve as a basis for weak learners.