Home ›
Entities
› academia
› Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data
Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data
Research article (Medical Physics, 2023) · cited 13× · AI/ML
Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data
Summary
Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data is a scholarly article[1].
Key Facts
Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data. Retrieved May 24, 2026, from https://4ort.xyz/entity/impact-of-imperfection-in-medical-imaging-data-on-deep-learningbased-segmentation-performance-an-experimental-study-usin
MLA“Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/impact-of-imperfection-in-medical-imaging-data-on-deep-learningbased-segmentation-performance-an-experimental-study-usin.
BibTeX@misc{4ortxyz_impact-of-imperfection-in-medical-imaging-data-on-deep-learningbased-segmentation-performance-an-experimental-study-usin_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data}}, year = {2026}, url = {https://4ort.xyz/entity/impact-of-imperfection-in-medical-imaging-data-on-deep-learningbased-segmentation-performance-an-experimental-study-usin}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Impact of imperfection in medical imaging data on deep learning‐based segmentation performance: An experimental study using synthesized data — https://4ort.xyz/entity/impact-of-imperfection-in-medical-imaging-data-on-deep-learningbased-segmentation-performance-an-experimental-study-usin (retrieved 2026-05-24)
