activity
20152022
most citedA Comparative Study of CNN, BoVW and LBP for Classification of Histopathological Images

25 citations · 144 across the 34 of their papers we have counts for

collaborators

58 papers

cs.CV2022

Learning Binary and Sparse Permutation-Invariant Representations for Fast and Memory Efficient Whole Slide Image Search

Sobhan Hemati, Shivam Kalra, Morteza Babaie +1

Learning suitable Whole slide images (WSIs) representations for efficient retrieval systems is a non-trivial task. The WSI embeddings obtained from current methods are in Euclidean…

eess.IV2022

Hospital-Agnostic Image Representation Learning in Digital Pathology

Milad Sikaroudi, Shahryar Rahnamayan, H. R. Tizhoosh

Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference in procedures to acquire WSIs at various trial sites gives rise to variability i…

eess.IV20221 cited

Learning to Predict RNA Sequence Expressions from Whole Slide Images with Applications for Search and Classification

Amir Safarpoor, Jason D. Hipp, H. R. Tizhoosh

Deep learning methods are widely applied in digital pathology to address clinical challenges such as prognosis and diagnosis. As one of the most recent applications, deep models ha…

cs.CV20223 cited

LILE: Look In-Depth before Looking Elsewhere -- A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archives

Danial Maleki, H. R Tizhoosh

The volume of available data has grown dramatically in recent years in many applications. Furthermore, the age of networks that used multiple modalities separately has practically…

cs.CV2021

Beyond Neighbourhood-Preserving Transformations for Quantization-Based Unsupervised Hashing

Sobhan Hemati, H. R. Tizhoosh

An effective unsupervised hashing algorithm leads to compact binary codes preserving the neighborhood structure of data as much as possible. One of the most established schemes for…

eess.IV2021

Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks

Nitish Bhatt, David Ramon Prados, Nedim Hodzic +2

Lung nodules are commonly missed in chest radiographs. We propose and evaluate P-AnoGAN, an unsupervised anomaly detection approach for lung nodules in radiographs. P-AnoGAN modifi…