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ZENODO
Dataset . 2024
License: CC BY NC SA
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY NC SA
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY NC SA
Data sources: Datacite
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CT Scans of Spine with Metastases (Lytic, Sclerotic)

Authors: Edelmers, Edgars;

CT Scans of Spine with Metastases (Lytic, Sclerotic)

Abstract

This dataset comprises 38 CT scans of the spine with identified and segmented metastatic lesions, focusing on two types of metastases: lytic and sclerotic. The dataset was used in the research article, "Artificial Intelligence Assisted Detection and Localization of Spinal Metastases." Each CT scan includes detailed metadata, such as: Type of Metastasis: Classified as either lytic or sclerotic. Primary Site of Metastasis: The original location of the cancer that metastasized to the spine, including sites such as melanoma, lungs, ovary, breast, prostate, kidney, blader, large intestine, multiple myeloma, stomach. Sex: Patient gender (male or female). This dataset was collected for research purposes and can serve as a valuable resource for further studies in oncology, radiology, and artificial intelligence-assisted diagnostics. The dataset is anonymized to ensure patient confidentiality. Edelmers, E.; Ņikuļins, A.; Sprūdža, K.L.; Stapulone, P.; Pūce, N.S.; Skrebele, E.; Siņicina, E.E.; Cīrule, V.; Kazuša, A.; Boločko, K. AI-Assisted Detection and Localization of Spinal Metastatic Lesions. Diagnostics 2024, 14, 2458. https://doi.org/10.3390/diagnostics14212458

Keywords

AI, oncology, lytic metastases, ML, radiology, sclerotic metastases, CT

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities
Cancer Research