Titlebook: Bildverarbeitung für die Medizin 2017; Algorithmen - System Klaus Hermann Maier-Hein, geb. Fritzsche,Thomas Ma Conference proceedings 2017

不妥協(xié)

宏偉

https://doi.org/10.1007/978-981-15-0882-0 the need of prior geometric calibration. Quantitative and qualitative evaluations on a numerical phantom as well as clinical data, show superior results compared to the current state-of-the-art method. Moreover, the clinical workflow is improved, as a dedicated system calibration for weight-bearing acquisitions is no longer required.

鋼盔

浪費(fèi)時(shí)間

amyloid

Skin Detection and Tracking for Camera-Based Photoplethysmography Using a Bayesian Classifier and Ln and heart rate (HR)estimation. The results showed that our method can detect and track suitable skin regions. We achieved a median HR detection rate of 80% which was only 6% lower than when applying manually defined ROIs.

發(fā)出眩目光芒

Self-Calibration and Simultaneous Motion Estimation for C-Arm CT Using Fiducial, the need of prior geometric calibration. Quantitative and qualitative evaluations on a numerical phantom as well as clinical data, show superior results compared to the current state-of-the-art method. Moreover, the clinical workflow is improved, as a dedicated system calibration for weight-bearing acquisitions is no longer required.

Humble

1431-472X Industrie und AnwendernIn den letzten Jahren hat sich der Workshop "Bildverarbeitung für die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2017 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gespr?che zwischen Wissenschaftlern, Industrie und Anwen

brachial-plexus

Indah Piliyanti,Agni Alam Awirya will they gain more control over their personal health. It is difficult to predict the speed of change and impact of both big data and artificial intelligence on health care, but it is clear that changes will be tremendous.

補(bǔ)充

Pantry

Seyed Mostafa Mohaghghegh Damadies Framework für die übertragung von Vorwissen in Form von segmentierten Trainingsdaten auf ungesehene Patienten mit Hilfe eines neuen starken Klassifizierer vor: dieVantage Point Forests (VPF). ?hnlich zu Random Decision Forests (RDF) werden schnelle Berechnungszeiten von wenigen Sekunden erreicht.