Deep learning-enabled virtual histological staining of biological samples
Histological staining is the gold standard for tissue examination in clinical pathology and life-
science research, which visualizes the tissue and cellular structures using chromatic dyes or …
science research, which visualizes the tissue and cellular structures using chromatic dyes or …
Deepfakes generation and detection: State-of-the-art, open challenges, countermeasures, and way forward
Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …
modern tools such as Tensorflow or Keras, and open-source trained models, along with …
Paint by example: Exemplar-based image editing with diffusion models
Abstract Language-guided image editing has achieved great success recently. In this paper,
we investigate exemplar-guided image editing for more precise control. We achieve this …
we investigate exemplar-guided image editing for more precise control. We achieve this …
Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer
S Foersch, C Glasner, AC Woerl, M Eckstein… - Nature medicine, 2023 - nature.com
Although it has long been known that the immune cell composition has a strong prognostic
and predictive value in colorectal cancer (CRC), scoring systems such as the immunoscore …
and predictive value in colorectal cancer (CRC), scoring systems such as the immunoscore …
Expressive text-to-image generation with rich text
Plain text has become a prevalent interface for text-to-image synthesis. However, its limited
customization options hinder users from accurately describing desired outputs. For example …
customization options hinder users from accurately describing desired outputs. For example …
Editgan: High-precision semantic image editing
Generative adversarial networks (GANs) have recently found applications in image editing.
However, most GAN-based image editing methods often require large-scale datasets with …
However, most GAN-based image editing methods often require large-scale datasets with …
Benchmarking self-supervised learning on diverse pathology datasets
Computational pathology can lead to saving human lives, but models are annotation hungry
and pathology images are notoriously expensive to annotate. Self-supervised learning has …
and pathology images are notoriously expensive to annotate. Self-supervised learning has …
The impact of site-specific digital histology signatures on deep learning model accuracy and bias
Abstract The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital
histology. Deep learning (DL) models have been trained on TCGA to predict numerous …
histology. Deep learning (DL) models have been trained on TCGA to predict numerous …
Face x-ray for more general face forgery detection
In this paper we propose a novel image representation called face X-ray for detecting
forgery in face images. The face X-ray of an input face image is a greyscale image that …
forgery in face images. The face X-ray of an input face image is a greyscale image that …
Celeb-df: A large-scale challenging dataset for deepfake forensics
AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging
problem threatening the trustworthiness of online information. The need to develop and …
problem threatening the trustworthiness of online information. The need to develop and …