A survey on artificial intelligence in histopathology image analysis
Sign Up to like & getrecommendations! Published in 2022 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.1474
Abstract: The increasing adoption of the whole slide image (WSI) technology in histopathology has dramatically transformed pathologists' workflow and allowed the use of computer systems in histopathology analysis. Extensive research in Artificial Intelligence (AI) with a… read more here.
Keywords: artificial intelligence; histopathology image; histopathology; analysis ... See more keywords
Constrained Deep Weak Supervision for Histopathology Image Segmentation
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2017.2724070
Abstract: In this paper, we develop a new weakly supervised learning algorithm to learn to segment cancerous regions in histopathology images. This paper is under a multiple instance learning (MIL) framework with a new formulation, deep… read more here.
Keywords: image; weak supervision; histopathology; histopathology image ... See more keywords
Su-MICL: Severity-Guided Multiple Instance Curriculum Learning for Histopathology Image Interpretable Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2022.3188326
Abstract: Histopathology image classification plays a critical role in clinical diagnosis. However, due to the absence of clinical interpretability, most existing image-level classifiers remain impractical. To acquire the essential interpretability, lesion-level diagnosis is also provided, relying… read more here.
Keywords: multiple instance; classification; level; histopathology image ... See more keywords
A Federated Learning System for Histopathology Image Analysis with an Orchestral Stain-Normalization GAN.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on medical imaging"
DOI: 10.1109/tmi.2022.3221724
Abstract: Currently, data-driven based machine learning is considered one of the best choices in clinical pathology analysis, and its success is subject to the sufficiency of digitized slides, particularly those with deep annotations. Although centralized training… read more here.
Keywords: system; stain; federated learning; histopathology image ... See more keywords
Breast cancer histopathology image classification through assembling multiple compact CNNs
Sign Up to like & getrecommendations! Published in 2019 at "BMC Medical Informatics and Decision Making"
DOI: 10.1186/s12911-019-0913-x
Abstract: BackgroundBreast cancer causes hundreds of thousands of deaths each year worldwide. The early stage diagnosis and treatment can significantly reduce the mortality rate. However, the traditional manual diagnosis needs intense workload, and diagnostic errors are… read more here.
Keywords: histopathology; breast cancer; model; histopathology image ... See more keywords
Large-scale tissue histopathology image segmentation based on feature pyramid
Sign Up to like & getrecommendations! Published in 2018 at "EURASIP Journal on Image and Video Processing"
DOI: 10.1186/s13640-018-0320-8
Abstract: Histopathology image analysis is a gold standard for cancer recognition and diagnosis. But typical problems with histopathology images that hamper automatic analysis include complex clinical features, insufficient training data, and large size of a single… read more here.
Keywords: image; segmentation; histopathology; histopathology image ... See more keywords