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Neural network for analyzing prostate cancer tissue microarrays

Problems and possibilities
 
: Bauer, Markus; Zürner, Sebastian; Popp, Georg; Kristiansen, Glen; Braumann, Ulf-Dietrich

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Tolxdorff, T.:
Bildverarbeitung für die Medizin 2020 : Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin
Wiesbaden: Springer Fachmedien, 2020 (Informatik aktuell)
ISBN: 978-3-658-29266-9 (Print)
ISBN: 978-3-658-29267-6 (Online)
pp.20-25
Workshop Bildverarbeitung für die Medizin (BVM) <2020, Berlin>
English
Conference Paper
Fraunhofer IZI ()
Gewebe; biopsy; calcium compounds; Krankheit; neural networks; phosphorus compounds; Urologie; glass microscope slides; histological section; laboratory protocols; malignant tissues; proof of concept; prostate cancers; radical prostatectomy; tissue microarrays

Abstract
Prostate cancer (PCa) is the dominating malignant tumor for men worldwide and across all ethnic groups. If a carcinoma is being suspected, e.g. due to blood levels, trans-rectal punch biopsies of the prostate will be accomplished, while in case of higher stages of the disease the complete prostate is being surgically removed (radical prostatectomy). In both cases prostate tissue will be prepared into histological sections on glass microscope slides according to certain laboratory protocols, and is finally microscopically inspected by a trained histopathologist. Even though this method is well established, it can lead to various problems because of objectivity deficiencies. In this paper, we present a proof of concept of using Artificial Neural Networks (ANN) for automatically analyzing prostate cancer tissue and rating its malignancy using tissue microarrays (TMAs) of sampled benign and malignant tissue.

: http://publica.fraunhofer.de/documents/N-586285.html