research
∙
09/14/2023
When is a Foundation Model a Foundation Model
Recently, several studies have reported on the fine-tuning of foundation...
share
research
∙
08/07/2023
ALFA – Leveraging All Levels of Feature Abstraction for Enhancing the Generalization of Histopathology Image Classification Across Unseen Hospitals
We propose an exhaustive methodology that leverages all levels of featur...
research
∙
07/25/2023
An Investigation into Glomeruli Detection in Kidney H E and PAS Images using YOLO
Context: Analyzing digital pathology images is necessary to draw diagnos...
research
∙
04/24/2023
Immunohistochemistry Biomarkers-Guided Image Search for Histopathology
Medical practitioners use a number of diagnostic tests to make a reliabl...
research
∙
04/24/2023
Composite Biomarker Image for Advanced Visualization in Histopathology
Immunohistochemistry (IHC) biomarkers are essential tools for reliable c...
research
∙
04/15/2023
Ranking Loss and Sequestering Learning for Reducing Image Search Bias in Histopathology
Recently, deep learning has started to play an essential role in healthc...
research
∙
03/02/2023
Evolutionary Computation in Action: Feature Selection for Deep Embedding Spaces of Gigapixel Pathology Images
One of the main obstacles of adopting digital pathology is the challenge...
research
∙
08/21/2022
Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images
Federated learning (FL) is a decentralized method enabling hospitals to ...
research
∙
06/27/2022
Monitoring Shortcut Learning using Mutual Information
The failure of deep neural networks to generalize to out-of-distribution...
research
∙
04/05/2022
Hospital-Agnostic Image Representation Learning in Digital Pathology
Whole Slide Images (WSIs) in digital pathology are used to diagnose canc...
research
∙
03/26/2022
Learning to Predict RNA Sequence Expressions from Whole Slide Images with Applications for Search and Classification
Deep learning methods are widely applied in digital pathology to address...
research
∙
03/02/2022
LILE: Look In-Depth before Looking Elsewhere – A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archives
The volume of available data has grown dramatically in recent years in m...
research
∙
11/28/2021
Gram Barcodes for Histopathology Tissue Texture Retrieval
Recent advances in digital pathology have led to the need for Histopatho...
research
∙
10/01/2021
Beyond Neighbourhood-Preserving Transformations for Quantization-Based Unsupervised Hashing
An effective unsupervised hashing algorithm leads to compact binary code...
research
∙
08/04/2021
Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks
Lung nodules are commonly missed in chest radiographs. We propose and ev...
research
∙
07/29/2021
Automatic Multi-Stain Registration of Whole Slide Images in Histopathology
Joint analysis of multiple biomarker images and tissue morphology is imp...
research
∙
07/29/2021
A Similarity Measure of Histopathology Images by Deep Embeddings
Histopathology digital scans are large-size images that contain valuable...
research
∙
10/29/2020
Ink Marker Segmentation in Histopathology Images Using Deep Learning
Due to the recent advancements in machine vision, digital pathology has ...
research
∙
07/10/2020
Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem
Variants of Triplet networks are robust entities for learning a discrimi...
research
∙
07/04/2020
Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches
We analyze the effect of offline and online triplet mining for colorecta...
research
∙
05/10/2020
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study
As many algorithms depend on a suitable representation of data, learning...
research
∙
05/07/2020
Recognizing Magnification Levels in Microscopic Snapshots
Recent advances in digital imaging has transformed computer vision and m...
research
∙
04/05/2020
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
Siamese neural network is a very powerful architecture for both feature ...
research
∙
04/04/2020
Weighted Fisher Discriminant Analysis in the Input and Feature Spaces
Fisher Discriminant Analysis (FDA) is a subspace learning method which m...
research
∙
11/20/2019
Yottixel – An Image Search Engine for Large Archives of Histopathology Whole Slide Images
With the emergence of digital pathology, searching for similar images in...
research
∙
11/20/2019
Pan-Cancer Diagnostic Consensus Through Searching Archival Histopathology Images Using Artificial Intelligence
The emergence of digital pathology has opened new horizons for histopath...
research
∙
03/28/2019
Atrial Fibrillation Detection Using Deep Features and Convolutional Networks
Atrial fibrillation is a cardiac arrhythmia that affects an estimated 33...
research
∙
03/17/2019
Patch Clustering for Representation of Histopathology Images
Whole Slide Imaging (WSI) has become an important topic during the last ...
research
∙
03/17/2019
Deep Features for Tissue-Fold Detection in Histopathology Images
Whole slide imaging (WSI) refers to the digitization of a tissue specime...
research
∙
09/11/2018
Facial Recognition with Encoded Local Projections
Encoded Local Projections (ELP) is a recently introduced dense sampling ...
research
∙
04/30/2018
The Effects of Image Pre- and Post-Processing, Wavelet Decomposition, and Local Binary Patterns on U-Nets for Skin Lesion Segmentation
Skin cancer is a widespread, global, and potentially deadly disease, whi...
research
∙
04/27/2018
Auto-Detection of Safety Issues in Baby Products
Every year, thousands of people receive consumer product related injurie...
research
∙
10/11/2017
Local Radon Descriptors for Image Search
Radon transform and its inverse operation are important techniques in me...
research
∙
10/11/2017
Convolutional Neural Networks for Histopathology Image Classification: Training vs. Using Pre-Trained Networks
We explore the problem of classification within a medical image data-set...
research
∙
09/28/2017
Fast Barcode Retrieval for Consensus Contouring
Marking tumors and organs is a challenging task suffering from both inte...
research
∙
09/27/2017
A Comparative Study of CNN, BoVW and LBP for Classification of Histopathological Images
Despite the progress made in the field of medical imaging, it remains a ...
research
∙
09/27/2017
Combining Real-Valued and Binary Gabor-Radon Features for Classification and Search in Medical Imaging Archives
Content-based image retrieval (CBIR) of medical images in large datasets...
research
∙
09/27/2017
Skin Lesion Segmentation: U-Nets versus Clustering
Many automatic skin lesion diagnosis systems use segmentation as a prepr...
research
∙
09/27/2017
Learning Autoencoded Radon Projections
Autoencoders have been recently used for encoding medical images. In thi...
research
∙
05/22/2017
Classification and Retrieval of Digital Pathology Scans: A New Dataset
In this paper, we introduce a new dataset, Kimia Path24, for image class...
research
∙
01/02/2017
Retrieving Similar X-Ray Images from Big Image Data Using Radon Barcodes with Single Projections
The idea of Radon barcodes (RBC) has been introduced recently. In this p...
research
∙
10/02/2016
Stacked Autoencoders for Medical Image Search
Medical images can be a valuable resource for reliable information to su...
research
∙
10/02/2016
MinMax Radon Barcodes for Medical Image Retrieval
Content-based medical image retrieval can support diagnostic decisions b...
research
∙
09/16/2016
Learning Opposites Using Neural Networks
Many research works have successfully extended algorithms such as evolut...
research
∙
09/16/2016
Radon-Gabor Barcodes for Medical Image Retrieval
In recent years, with the explosion of digital images on the Web, conten...
research
∙
04/16/2016
Radon Features and Barcodes for Medical Image Retrieval via SVM
For more than two decades, research has been performed on content-based ...
research
∙
09/15/2015
Self-Configuring and Evolving Fuzzy Image Thresholding
Every segmentation algorithm has parameters that need to be adjusted in ...
research
∙
09/15/2015
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data
Good results on image classification and retrieval using support vector ...
research
∙
07/05/2015