Szczegóły publikacji
Opis bibliograficzny
Lytic region recognition in hip radiograms by means of statistical dominance transform / Marcin Kociołek, Adam PIÓRKOWSKI, Rafał Obuchowicz, Paweł Kamiński, Michał Strzelecki // W: Computer vision and graphics : international conference : ICCVG 2018 : Warsaw, Poland, September 17–19, 2018 : proceedings / eds. Leszek J. Chmielewski [et al.]. — [Cham] : Springer International Publishing, cop. 2018. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 11114. Image Processing, Computer Vision, Pattern Recognition, and Graphics). — ISBN: 978-3-030-00691-4; e-ISBN: 978-3-030-00692-1. — S. 349–360. — Bibliogr. s. 359–360, Abstr. — Publikacja dostępna online od: 2018-09-14
Autorzy (5)
- Kociołek Marcin
- AGHPiórkowski Adam
- Obuchowicz Rafał
- Kamiński Paweł
- Strzelecki Michał
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 117888 |
|---|---|
| Data dodania do BaDAP | 2018-11-19 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-030-00692-1_31 |
| Rok publikacji | 2018 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Computer Vision and Graphics 2018 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
Total hip replacement is the accepted treatment procedure of the end stage degeneration of the hip joint. Instability of the prosthesis might be recognized on the radiographic images as area of bone radio - lucency adjacent to the prosthesis pin. However, the very important issue of radiological recognition of periprosthetic lucent areas reflecting the lysis remains a challenge. Small dimensions and fuzzy borders of the lytic areas makes them difficult regions to recognize. Additional factors as high BMI of the patients and/or radiograms taken through a mattress can make the evaluation even more difficult, while small lucent areas might be additionally blurred and of very low contrast. The paper presents a new approach for quantitative recognition of preprothetic lytic areas. We have proposed a multistep algorithm utilizing Statistical Dominance Transform for detection of lytic areas on digital radiograms. Preliminary results are quite promising. It was demonstrated that location and shape of the detected lytic region is in good agreement with assessment by radiologists.
