T ITLE :
T EAM : M ÉTHODES FONCTIONNELLES , QUANTITATIVES ET MOLÉCULAIRES POUR L
’
IMAGERIE ULTRASONORE
HTTP :// WWW .
LABOS .
UPMC .
FR / LIP /
T HESIS A DVISOR : S.
L ORI BRIDAL
C O -A DVISORS : A LAIN CORON , F RÉDERIQUE F ROUIN
– INSERM U678
Introduction : The Parametric Imaging Laboratory has established experience in the study of tumor angiogenesis and therapy in murine tumor models. The evolution of tumors and their vascularization can be followed with functional and molecular ultrasonic contrast imaging. Quantitative analysis of the image sequences obtained after contrast injection (2 spatial dimensions + time) is applied to estimate the evolution of the pixel intensity in a region of interest as a function of time. The variation of this intensity with time can be linked to blood flow, fractional blood volume and relative viability of the tumor. The quality of the information obtained by this approach depends on the (time-varying) signal-to-noise ratio and the uniformity of the ultrasound field in the selected regions of interest.
Approach : This project aims to develop methods that will improve region of interest segmentation on sequences of ultrasound contrast images and that will provide more robust quantitative evaluation of contrast up-take.
Segmentation techniques will be developed and tested using an existing data base of contrast sequences acquired in murine tumors during anti-angiogenic therapy (therapy preventing vascular formation).
On these data (2D+T), the student will implement methods for image registration and segmentation and validate software for the identification of regions of interest in tumors suitable for quantitative contrast analysis. Final validation will be based on analysis of the time-intensity curves from selected regions of interest using mathematical models for flow and information related to evolution of statistics of the pixel distribution. In addition to optimization for estimation performance, the algorithm will be optimized for best compromise between segmentation quality and acceptable calculation time.
The performance of the resulting registration and segmentation tool will be evaluated on independent data series. Criteria will include verification of the correspondence between results obtained from the in vivo data and histological reference data.
Anticipated results : Development of reliable and automatic or semi-automatic techniques will allow more rapid analysis of ultrasound contrast sequences and should eliminate an important source of inter-operator variability. Once the techniques are validated, their integration into analysis software should provide better and more quantitative exploitation of the information provided by this imaging mode.
P ROFILE D ESIRED : A PPLIED MATH , O PTIMIZATION , I MAGE A NALYSIS , M AT L AB .
E XPERIENCE WITH M EDICAL IMAGING AND
C++ WILL BE APPRECIATED
P LEASE CONTACT : S.
L ORI B RIDAL
E MAIL : L ORI .B
RIDAL @ UPMC .
FR
T ELEPHONE : 01 44 41 96 05