Data · dataset · 2024
Primary Liver Cancer CECT Imaging Dataset
Listed in ScienceDB
Primary liver cancer is a significant global health issue, characterized by high incidence and mortality rates worldwide.
Description
Accurate diagnosis and classification of subtypes are essential for selecting appropriate treatment options and enhancing patient outcomes. Contrast-enhanced computed tomography (CECT) has proven highly sensitive and specific in diagnosing liver cancer.
Currently, publicly available datasets of liver cancer CECT scans are limited and often do not comprehensively cover liver cancer subtypes or include complete phasing of CT scans. We hypothesize that utilizing full-phase 3D CECT images, including the Plain, Arterial, Venous, and Delayed phases, can improve the diagnostic classification performance for liver cancer. To test this hypothesis, we have collected a large dataset from a single medical institution that includes 275 cases of liver cancer, featuring Hepatocellular Carcinoma (HCC), Intrahepatic Cholangiocarcinoma (ICC), and Combined Hepatocellular-Cholangiocarcinoma (cHCC-CCA), as well as CECT images from 83 non-liver cancer subjects.
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For each patient, we annotated the liver and lesion regions. This dataset, rich in liver cancer types and complete in CT phasing, facilitates the development and validation of diagnostic classification models and lesion segmentation models tailored to liver cancer CT imaging.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.12173 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Cancer 75% · Computed tomography 75% · Image 65% · Imaging 75% · Oncology and carcinogenesis 69%
Provenance · 1 source records, 17 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.12173 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:3211 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:ct | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:imaging | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |