Skip to Main content Skip to Navigation
Book sections

Validation and evaluation metrics for medical and biomedical image synthesis

Abstract : Synthetic image data play an important role in the verification of medical and biomedical image analysis algorithms. However the usage of such data strongly relies on their quality and plausibility. Despite the emergence of many frameworks for image synthesis in recent years, the quality of the generated images has not been sufficiently assessed in many cases, or the methodology varied across the publications. If we want to use synthetic image data for the verification of biomedical analysis tools, then the images should resemble the real ones as much as possible with evidence about their similarity. Initially, the hardware available for simulations was limited. Therefore, the validation was not under the scope of interest. With the technological improvements, the expectations put on synthetic data have arisen. Proper validation of synthetic image data is nowadays becoming essential.
Document type :
Book sections
Complete list of metadata

https://hal.inria.fr/hal-03721947
Contributor : Ninon Burgos Connect in order to contact the contributor
Submitted on : Monday, July 18, 2022 - 4:39:08 PM
Last modification on : Friday, August 5, 2022 - 2:29:56 PM

File

BISS-Chapter25-Validation_eval...
Files produced by the author(s)

Identifiers

Citation

Tereza Nečasová, Ninon Burgos, David Svoboda. Validation and evaluation metrics for medical and biomedical image synthesis. Biomedical Image Synthesis and Simulation, Elsevier, pp.573-600, 2022, 978-0-12-824349-7. ⟨10.1016/B978-0-12-824349-7.00032-3⟩. ⟨hal-03721947⟩

Share

Metrics

Record views

1112

Files downloads

4727