Machine learning in microscopy–insights, opportunities and challenges
Machine learning (ML) is transforming the field of image processing and analysis, from
automation of laborious tasks to open-ended exploration of visual patterns. This has striking …
automation of laborious tasks to open-ended exploration of visual patterns. This has striking …
Applications of Digital Pathology in Cancer: A Comprehensive Review
M Omar, MK Alexanderani, I Valencia… - Annual Review of …, 2024 - annualreviews.org
Digital pathology, powered by whole-slide imaging technology, has the potential to
transform the landscape of cancer research and diagnosis. By converting traditional …
transform the landscape of cancer research and diagnosis. By converting traditional …
Diffinfinite: Large mask-image synthesis via parallel random patch diffusion in histopathology
We present DiffInfinite, a hierarchical diffusion model that generates arbitrarily large
histological images while preserving long-range correlation structural information. Our …
histological images while preserving long-range correlation structural information. Our …
[HTML][HTML] Speed, accuracy, and efficiency: The promises and practices of digitization in pathology
Digitization is often presented in policy discourse as a panacea to a multitude of
contemporary problems, not least in healthcare. How can policy promises relating to …
contemporary problems, not least in healthcare. How can policy promises relating to …
[HTML][HTML] Report of the Medical Image De-Identification (MIDI) Task Group-Best Practices and Recommendations
1.4 Support This project has been funded in whole or in part with Federal funds from the
National Cancer Institute, National Institutes of Health, under Contract No …
National Cancer Institute, National Institutes of Health, under Contract No …
Balancing privacy and progress in artificial intelligence: anonymization in histopathology for biomedical research and education
The advancement of biomedical research heavily relies on access to large amounts of
medical data. In the case of histopathology, Whole Slide Images (WSI) and …
medical data. In the case of histopathology, Whole Slide Images (WSI) and …
Digital pathology implementation in cancer diagnostics: towards informed decision-making
O Sulaieva, O Dudin, O Koshyk, M Panko… - Frontiers in Digital …, 2024 - frontiersin.org
Digital pathology (DP) has become a part of the cancer healthcare system, creating
additional value for cancer patients. DP implementation in clinical practice provides plenty of …
additional value for cancer patients. DP implementation in clinical practice provides plenty of …
Summary of the National Cancer Institute 2023 virtual workshop on medical image de-identification—part 2: pathology whole slide image de-identification, de-facing …
De-identification of medical images intended for research is a core requirement for data
sharing initiatives, particularly as the demand for data for artificial intelligence (AI) …
sharing initiatives, particularly as the demand for data for artificial intelligence (AI) …
Anonymization of whole slide images in histopathology for research and education
T Bisson, M Franz, I Dogan O, D Romberg… - Digital …, 2023 - journals.sagepub.com
Objective The exchange of health-related data is subject to regional laws and regulations,
such as the General Data Protection Regulation (GDPR) in the EU or the Health Insurance …
such as the General Data Protection Regulation (GDPR) in the EU or the Health Insurance …
Continual Domain Incremental Learning for Privacy-Aware Digital Pathology
In recent years, there has been remarkable progress in the field of digital pathology, driven
by the ability to model complex tissue patterns using advanced deep-learning algorithms …
by the ability to model complex tissue patterns using advanced deep-learning algorithms …