Big data in basic and translational cancer research
Historically, the primary focus of cancer research has been molecular and clinical studies of
a few essential pathways and genes. Recent years have seen the rapid accumulation of …
a few essential pathways and genes. Recent years have seen the rapid accumulation of …
Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects
Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to
bring medicine from the era of 'sick-care'to the era of healthcare and prevention. The …
bring medicine from the era of 'sick-care'to the era of healthcare and prevention. The …
Foundation model for cancer imaging biomarkers
Foundation models in deep learning are characterized by a single large-scale model trained
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …
Monai label: A framework for ai-assisted interactive labeling of 3d medical images
The lack of annotated datasets is a major bottleneck for training new task-specific
supervised machine learning models, considering that manual annotation is extremely …
supervised machine learning models, considering that manual annotation is extremely …
The bioimage archive–building a home for life-sciences microscopy data
M Hartley, GJ Kleywegt, A Patwardhan… - Journal of Molecular …, 2022 - Elsevier
Despite the huge impact of data resources in genomics and structural biology, until now
there has been no central archive for biological data for all imaging modalities. The …
there has been no central archive for biological data for all imaging modalities. The …
MITI minimum information guidelines for highly multiplexed tissue images
The imminent release of tissue atlases combining multichannel microscopy with single-cell
sequencing and other omics data from normal and diseased specimens creates an urgent …
sequencing and other omics data from normal and diseased specimens creates an urgent …
National Cancer Institute Imaging Data Commons: toward transparency, reproducibility, and scalability in imaging artificial intelligence
The remarkable advances of artificial intelligence (AI) technology are revolutionizing
established approaches to the acquisition, interpretation, and analysis of biomedical …
established approaches to the acquisition, interpretation, and analysis of biomedical …
[HTML][HTML] Thirty years of the DICOM standard
M Larobina - Tomography, 2023 - mdpi.com
Digital Imaging and Communications in Medicine (DICOM) is an international standard that
defines a format for storing medical images and a protocol to enable and facilitate data …
defines a format for storing medical images and a protocol to enable and facilitate data …
NCI cancer research data commons: resources to share key cancer data
Z Wang, TM Davidsen, GR Kuffel, KD Addepalli… - Cancer …, 2024 - aacrjournals.org
Since 2014, the NCI has launched a series of data commons as part of the Cancer Research
Data Commons (CRDC) ecosystem housing genomic, proteomic, imaging, and clinical data …
Data Commons (CRDC) ecosystem housing genomic, proteomic, imaging, and clinical data …
Must-have qualities of clinical research on artificial intelligence and machine learning
In the field of computer science, known as artificial intelligence, algorithms imitate reasoning
tasks that are typically performed by humans. The techniques that allow machines to learn …
tasks that are typically performed by humans. The techniques that allow machines to learn …