Szczegóły publikacji
Opis bibliograficzny
A computationally optimized procedure based on discrete wavelet transform supporting analysis of medical images / Zofia Długosz, Michał Długosz, Michał Rajewski, Piotr BOGACKI , Aleksandra Śniatkowska, Janusz Winiecki, Tomasz Talaśka, Alicja Bartkowska-Śniatkowska, Rafał Długosz // Journal of Computational and Applied Mathematics ; ISSN 0377-0427 . — 2026 — vol. 472 art. no. 116774, s. 1–14. — Bibliogr. s. 14. — Publikacja dostępna online od: 2025-06-02. — P. Bogacki – dod. afiliacja: Aptiv Services Poland, Technical Centre Kraków, Poland
Autorzy (9)
- Długosz Zofia
- Długosz Michał
- Rajewski Michał
- AGHBogacki Piotr
- Śniatkowska Aleksandra
- Winiecki Janusz
- Talaśka Tomasz
- Bartkowska-Śniatkowska Alicja
- Długosz Rafał
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 168897 |
|---|---|
| Data dodania do BaDAP | 2026-07-30 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.cam.2025.116774 |
| Rok publikacji | 2026 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Computational and Applied Mathematics |
Abstract
The paper presents a concept and implementation of an algorithm whose task is to automatically determine the outline of a spot representing cancerous tissue. We assume that the location of this tissue was previously determined based on data obtained during computed tomography (CT). In medical images obtained on the basis of CT, active areas are represented by spots of appropriate intensity. For the purposes of properly selected radiotherapy, it is necessary to determine the outline of these areas. At the same time, it is very important to maintain an appropriate margin around the main area where the cancer occurs, so as not to miss small cancer foci located near the larger area. The aim of the proposed method is to process the biomedical image in such a way that the mentioned small foci are not lost, but are located inside the outline designated with an appropriate margin. The algorithm is based on a modified wavelet transform and appropriately selected linear and nonlinear filters with the possibility of their returning. The algorithm was, as a prototype, implemented in the Matlab environment and verified on images selected so that they were representative for various situations. The system for which the proposed algorithm is being developed operates in real time. For this reason, we paid special attention to the problem of computational complexity of its particular stages. This is also important because during a medical procedure we deal with a series of biomedical images, creating a 3-D structure. Savings in this area obtained for a single image therefore give measurable benefits for the entire set of images.
