160 citations · 607 across the 73 of their papers we have counts for
11 papers · 1 filter
Decentralized Federated Learning through Proxy Model Sharing
Shivam Kalra, Junfeng Wen, Jesse C. Cresswell +2
Institutions in highly regulated domains such as finance and healthcare often have restrictive rules around data sharing. Federated learning is a distributed learning framework tha…
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…
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…
Automatic Multi-Stain Registration of Whole Slide Images in Histopathology
Abubakr Shafique, Morteza Babaie, Mahjabin Sajadi +3
Joint analysis of multiple biomarker images and tissue morphology is important for disease diagnosis, treatment planning and drug development. It requires cross-staining comparison…
A Similarity Measure of Histopathology Images by Deep Embeddings
Mehdi Afshari, H. R. Tizhoosh
Histopathology digital scans are large-size images that contain valuable information at the pixel level. Content-based comparison of these images is a challenging task. This study…
Histogram of Cell Types: Deep Learning for Automated Bone Marrow Cytology
Rohollah Moosavi Tayebi, Youqing Mu, Taher Dehkharghanian +5
Bone marrow cytology is required to make a hematological diagnosis, influencing critical clinical decision points in hematology. However, bone marrow cytology is tedious, limited t…
Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
Shivam Kalra, Mohammed Adnan, Sobhan Hemati +3
Deep learning methods such as convolutional neural networks (CNNs) are difficult to directly utilize to analyze whole slide images (WSIs) due to the large image dimensions. We over…
Colored Kimia Path24 Dataset: Configurations and Benchmarks with Deep Embeddings
Sobhan Shafiei, Morteza Babaie, Shivam Kalra +1
The Kimia Path24 dataset has been introduced as a classification and retrieval dataset for digital pathology. Although it provides multi-class data, the color information has been…
Searching for Pneumothorax in X-Ray Images Using Autoencoded Deep Features
Antonio Sze-To, Abtin Riasatian, Hamid R. Tizhoosh
Fast diagnosis and treatment of pneumothorax, a collapsed or dropped lung, is crucial to avoid fatalities. Pneumothorax is typically detected on a chest X-ray image through visual…
Fine-Tuning and Training of DenseNet for Histopathology Image Representation Using TCGA Diagnostic Slides
Abtin Riasatian, Morteza Babaie, Danial Maleki +19
Feature vectors provided by pre-trained deep artificial neural networks have become a dominant source for image representation in recent literature. Their contribution to the perfo…
Magnification Generalization for Histopathology Image Embedding
Milad Sikaroudi, Benyamin Ghojogh, Fakhri Karray +2
Histopathology image embedding is an active research area in computer vision. Most of the embedding models exclusively concentrate on a specific magnification level. However, a use…