Tissue phenotyping is a fundamental computational pathology (CPath) task...
Human tissue and its constituent cells form a microenvironment that is
f...
The accelerated adoption of digital pathology and advances in deep learn...
Contrastive visual language pretraining has emerged as a powerful method...
Integrating whole-slide images (WSIs) and bulk transcriptomics for predi...
The recent explosion of interest in multimodal applications has resulted...
Multiple Instance Learning (MIL) is a widely employed framework for lear...
Supervised learning tasks such as cancer survival prediction from gigapi...
Vision Transformers (ViTs) and their multi-scale and hierarchical variat...
In the current development and deployment of many artificial intelligenc...
The rapidly emerging field of deep learning-based computational patholog...
The expanding adoption of digital pathology has enabled the curation of ...
Cancer prognostication is a challenging task in computational pathology ...
Frozen sectioning (FS) is the preparation method of choice for microscop...
Deep Learning-based computational pathology algorithms have demonstrated...
Cancers of unknown primary (CUP), represent 1-3
enigmatic disease where ...
The rapidly emerging field of computational pathology has the potential ...
Cancer diagnosis, prognosis and therapeutic response predictions are bas...
Histology-based grade classification is clinically important for many ca...
Convolutional neural networks can be trained to perform histology slide
...
Medical endoscopy remains a challenging application for simultaneous
loc...
We present a deep learning framework for wide-field, content-aware estim...
We propose the fusion discriminator, a single unified framework for
inco...
Humans make accurate decisions by interpreting complex data from multipl...
We present a deep learning approach for laser speckle reduction ('DeepLS...
Nuclei segmentation is a fundamental task that is critical for various
c...
Monocular depth estimation is an extensively studied computer vision pro...
Deep learning has emerged as a powerful artificial intelligence tool to
...
To realize the full potential of deep learning for medical imaging, larg...
Colorectal cancer is the fourth leading cause of cancer deaths worldwide...
Sparsity exploiting image reconstruction (SER) methods have been extensi...
Two-Dimensional (2D) Discrete Fourier Transform (DFT) is a basic and
com...
Limited data and low dose constraints are common problems in a variety o...