ArticleScientific reports2019
Using the Sonification for Hardly Detectable Details in Medical Images.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A Dual Stream Deep Learning Framework for Alzheimer's Disease Detection Using MRI Sonification.Journal of imaging · 2026Article
- Sensory Representation of Neural Networks Using Sound and Color for Medical Imaging Segmentation.Journal of imaging · 2025Article
- Higher-order sonification of the human brain.Scientific reports · 2025Article
- On the flexible needle insertion into the human liver.Scientific reports · 2021Article
- Using the Sonification for Hardly Detectable Details in Medical Images.Scientific reports · 2019Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The inverse sonification problem is investigated in this article in order to detect hardly capturing details in a medical image. The direct problem consists in converting the image data into sound signals by a transformation which involves three steps - data, acoustics parameters and sound representations. The inverse problem is reversing back the sound signals into image data. By using the known sonification operator, the inverse approach does not bring any gain in the sonified medical imaging. The replication of the image already known does not help the diagnosis and surgical operation. In order to bring gains in the medical imaging, a new sonification operator is advanced in this paper, by using the Burgers equation of sound propagation. The sonified medical imaging is useful in interpreting the medical imaging that, however powerful they may be, are never good enough to aid tumour surgery. The inverse approach is exercised on several medical images used to surgical operations.
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Registered trials
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