A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images
Mitosis counting of biopsies is an important biomarker for breast cancer patients, which
supports disease prognostication and treatment planning. Developing a robust mitotic cell …
supports disease prognostication and treatment planning. Developing a robust mitotic cell …
Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings
SC Huang, CC Chen, J Lan, TY Hsieh… - Nature …, 2022 - nature.com
The pathological identification of lymph node (LN) metastasis is demanding and tedious.
Although convolutional neural networks (CNNs) possess considerable potential in …
Although convolutional neural networks (CNNs) possess considerable potential in …
Rankmix: Data augmentation for weakly supervised learning of classifying whole slide images with diverse sizes and imbalanced categories
Abstract Whole Slide Images (WSIs) are usually gigapixel in size and lack pixel-level
annotations. The WSI datasets are also imbalanced in categories. These unique …
annotations. The WSI datasets are also imbalanced in categories. These unique …
CS-CO: A hybrid self-supervised visual representation learning method for H&E-stained histopathological images
Visual representation extraction is a fundamental problem in the field of computational
histopathology. Considering the powerful representation capacity of deep learning and the …
histopathology. Considering the powerful representation capacity of deep learning and the …
Domain generalization for medical image analysis: A survey
Medical Image Analysis (MedIA) has become an essential tool in medicine and healthcare,
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
Understanding hessian alignment for domain generalization
Abstract Out-of-distribution (OOD) generalization is a critical ability for deep learning models
in many real-world scenarios including healthcare and autonomous vehicles. Recently …
in many real-world scenarios including healthcare and autonomous vehicles. Recently …
Colour adaptive generative networks for stain normalisation of histopathology images
Deep learning has shown its effectiveness in histopathology image analysis, such as
pathology detection and classification. However, stain colour variation in Hematoxylin and …
pathology detection and classification. However, stain colour variation in Hematoxylin and …
[HTML][HTML] Computer-assisted diagnosis of lymph node metastases in colorectal cancers using transfer learning with an ensemble model
A Khan, N Brouwer, A Blank, F Müller, D Soldini… - Modern pathology, 2023 - Elsevier
Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task,
but it is amenable to artificial intelligence (AI)-assisted diagnostic solution. Here, we propose …
but it is amenable to artificial intelligence (AI)-assisted diagnostic solution. Here, we propose …
Artifact-based domain generalization of skin lesion models
Deep Learning failure cases are abundant, particularly in the medical area. Recent studies
in out-of-distribution generalization have advanced considerably on well-controlled synthetic …
in out-of-distribution generalization have advanced considerably on well-controlled synthetic …
Unsupervised domain adaptation using feature disentanglement and GCNs for medical image classification
The success of deep learning has set new benchmarks for many medical image analysis
tasks. However, deep models often fail to generalize in the presence of distribution shifts …
tasks. However, deep models often fail to generalize in the presence of distribution shifts …