Search results for "US imaging"
showing 4 items of 4 documents
Design and characterization of the SiPM tracking system of NEXT-DEMO, a demonstrator prototype of the NEXT-100 experiment
2013
NEXT-100 experiment aims at searching the neutrinoless double-beta decay of the Xe-136 isotope using a TPC filled with a 100 kg of high-pressure gaseous xenon, with 90% isotopic enrichment. The experiment will take place at the Laboratorio Subterraneo de Canfranc (LSC), Spain. NEXT-100 uses electroluminescence (EL) technology for energy measurement with a resolution better than 1% FWHM. The gaseous xenon in the TPC additionally allows the tracks of the two beta particles to be recorded, which are expected to have a length of up to 30 cm at 10 bar pressure. The ability to record the topological signature of the beta beta 0 nu events provides a powerful background rejection factor for the bet…
The upgrade of the ALICE TPC with GEMs and continuous readout
2020
Journal of Instrumentation 16(03), P03022 (2021). doi:10.1088/1748-0221/16/03/P03022
Electron drift properties in high pressure gaseous xenon
2018
[EN] Gaseous time projection chambers (TPC) are a very attractive detector technology for particle tracking. Characterization of both drift velocity and di¿usion is of great importance to correctly assess their tracking capabilities. NEXT-White is a High Pressure Xenon gas TPC with electroluminescent ampli¿cation, a 1:2 scale model of the future NEXT-100detector, which will be dedicated to neutrinoless double beta decay searches. NEXT-White has been operating at Canfranc Underground Laboratory (LSC) since December2016. The drift parameters have been measured using 83mKr for a range of reduced drift ¿elds at two di¿erent pressure regimes, namely 7.2 bar and 9.1 bar. Theresults have been comp…
Segmentation d'images robuste appliqué à l'imagerie par résonance magnétique et l'échographie de la prostate
2012
Prostate segmentation in trans rectal ultrasound (TRUS) and magnetic resonanceimages (MRI) facilitates volume estimation, multi-modal image registration, surgicalplaning and image guided prostate biopsies. The objective of this thesis is to developshape and region prior deformable models for accurate, robust and computationallyefficient prostate segmentation in TRUS and MRI images. Primary contributionof this thesis is in adopting a probabilistic learning approach to achieve soft classificationof the prostate for automatic initialization and evolution of a shape andregion prior deformable models for prostate segmentation in TRUS images. Twodeformable models are developed for the purpose. An…