Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects.
Saved in:
| Title: | Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects. |
|---|---|
| Authors: | Negassi M; Department of Sustainable Systems Engineering INATECH, University of Freiburg, Emmy-Noether-Straße 2, Freiburg, Germany.; Department Object and Shape Detection, Fraunhofer Institute for Physical Measurement Techniques IPM, Heidenhofstraße 8, Freiburg, Germany., Suarez-Ibarrola R; Department of Urology, Faculty of Medicine, University of Freiburg-Medical Centre, Hugstetter Str. 55, Freiburg, Germany., Hein S; Department of Urology, Faculty of Medicine, University of Freiburg-Medical Centre, Hugstetter Str. 55, Freiburg, Germany., Miernik A; Department of Urology, Faculty of Medicine, University of Freiburg-Medical Centre, Hugstetter Str. 55, Freiburg, Germany., Reiterer A; Department of Sustainable Systems Engineering INATECH, University of Freiburg, Emmy-Noether-Straße 2, Freiburg, Germany. alexander.reiterer@ipm.fraunhofer.de.; Department Object and Shape Detection, Fraunhofer Institute for Physical Measurement Techniques IPM, Heidenhofstraße 8, Freiburg, Germany. alexander.reiterer@ipm.fraunhofer.de. |
| Source: | World journal of urology [World J Urol] 2020 Oct; Vol. 38 (10), pp. 2349-2358. Date of Electronic Publication: 2020 Jan 10. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Springer International Country of Publication: Germany NLM ID: 8307716 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1433-8726 (Electronic) Linking ISSN: 07244983 NLM ISO Abbreviation: World J Urol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
