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 • 15 Mar 2019 • Aditya Sriram, Shivam Kalra, H. R. Tizhoosh
This paper introduces the `Projectron' as a new neural network architecture that uses Radon projections to both classify and represent medical images.
no code implementations • 27 Sep 2017 • Aditya Sriram, Shivam Kalra, H. R. Tizhoosh, Shahryar Rahnamayan
Autoencoders have been recently used for encoding medical 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 • 16 Sep 2016 • Shivam Kalra, Aditya Sriram, Shahryar Rahnamayan, H. R. Tizhoosh
In this paper, we introduce an approach to learn type-II opposites from the given inputs and their outputs using the artificial neural networks (ANNs).