Target description

IMPACT Team: Image and models for target description

 

To augment pathophysiological target description and perception, patient specific analyzes are conducted.
In a patient-directed approach, reconstruction, description, characterization, localization and tracking of anatomical structures and lesions constitute the basis of the interventional planning and treatment delivery.

 

 

Reconstruction of spatiotemporal data

 

 

3D reconstruction of the coronary arterial tree in cardiac C-arm CBCT imaging:

X-ray imaging is a modality of reference at the pre-operative step, but alo in operating rooms or interventional environments. The rotational sensors are progressively considered as a standard three-dimensional embedded imaging for different types of therapies. This is particularly true for CBCT and rotational angiography systems. However, their use in the spatio-temporal context (cardiac and respiratory movements) remains a difficult problem.

Some recent publications:

  • - Chen Y., Yang J., Shu H., Shi L., Wu J., Luo L, Coatrieux J-L., Toumoulin C., 2-D Impulse Noise Suppression by Recursive  Gaussian Maximum Likelihood Estimation. PLoS One. 2014;9(5). 
  • - Yang G, Zhou J, Boulmier D, Garcia MP, Luo L, Toumoulin C. Characterization of 3D Coronary Tree Motion from MSCT Angiography. IEEE Transactions on Information Technology in Biomedicine. 2010;14(1):92-97.
  • - Hu Y, Xie L, Luo L,Nunes J-C, Toumoulin C. L0 constrained sparse reconstruction for multi-slice Helical CT reconstruction, Physics in Medicine and Biology journal. 2011;56(4):1173-89.

  • - Oukili A, Nunes JC, Yang C, Luo LM, Toumoulin C. Object-based 3D binary reconstruction from sparse projections in cone beam CT: Comparison of three projection operators, In Proceedings of the International Symposium on Biomedical imaging (ISBI): From Nano to Macro. 2013: 1276-1279.

 

Denoising, enhancement and analysis

 

Moment-based approaches for reconstruction, characterization and recognition:

Methodological research is conducted in collaboration with LIST-CRIBs to study moment-based approaches which present several possible applications such as reconstruction, characterization and recognition.

Some recent publications:

  • - Shu H, Chen BJ, Zhang H, Haigron P, Luo L. Fast Computation of Tchebichef Moments for Binary and Gray-Scale Images. IEEE Transactions on Image Processing. 2010;19(12):3171-80.
  • - Chen, Y., Y. Li, W. Yu, L. Luo, W. Chen and C. Toumoulin. Joint-MAP Tomographic Reconstruction with Patch Similarity Based Mixture Prior Model, Multiscale Model. Simul. 2011;9(4):1399-1419.
  • - Chen BJ, Shu HZ, Zhang H, Chen G, Toumoulin C, Dillenseger J-L, Luo LM. Quaternion Zernike Moments and Their Invariants for Color Image Analysis and Object Recognition. Signal Processing. 2012;92(2):308-18.
  • - Chen Y, Yang Z, Hu Y, Yang G, Zhu Y, Li Y, luo L, Chen W, Toumoulin C. “Thoracic Low-dose CT Image Processing Using an Artifact Suppressed Large-scale Nonlocal Means”, Physics in Medicine and Biology. 2012;57:2667–2688.
  • - Chen Y, Yin X, Shi L, Shu H, Luo L, Coatrieux JL, Toumoulin C., Improving abdomen tumor low-dose CT images using a fast dictionary learning based processing. Phys Med Biol. 2013 Aug 21;58(16):5803-20.
  • - Chen Y., Yang J., Shu H., Shi L., Wu J., Luo L, Coatrieux J-L., Toumoulin C., 2-D Impulse Noise Suppression by Recursive Gaussian Maximum Likelihood Estimation. PLoS One. 2014;9(5).
  • - Shao Z, Shu H, Wu J, Chen B, Coatrieux JL. Quaternion Bessel–Fourier Moments and Their Invariant Descriptors for Object Reconstruction and Recognition. Pattern Recognition. 2014;47(2):603-11.
  • - Li Y, Chen Y, Oukili A, Luo L, Chen W, Toumoulin C. Strategy of CT sinogram inpainting based on sinusoid-like curve decomposition and eigenvector-guided interpolation. Journal of the Optical Society of America A. 2012;29(1):153-163.

     

    Cardiac structures description and segmentation:

     

    A part of our work was devoted to coronary artery and vein segmentation from MSCT (dynamic and static) and MRI (static). We dealt with the issue of morphological analysis of degenerated aortic valve bioprostheses. We also worked on the segmentation of the left atrium in the context of non invasive transesophageal HIFU-based ablation of Atrial Fibrilation.

     

    Some recent publications:

    • - Garcia MP, Velut J, Boulmier D, Leclercq C, Garreau M, Haigron P, Toumoulin C. Coronary Vein Characterization From 4D MSCT by means of a Minimal Path technique and Geometrical Moments, IEEE Transactions on Information Technology in Biomedicine. 2013;5(2):336-345.
    • - Weese J, Groth A, Nickisch H, Barschdorf H, Weber FM, Velut J, Castro M, Toumoulin C, Coatrieux JL, De Craene M, Piella G, Tobon-Gomez C, Frangi AF, Barber DC, Valverde I, Shi Y, Staicu C, Brown A, Beerbaum P, Hose DR. Generating Anatomical Models of the Heart and the Aorta from Medical Images for Personalized Physiological Simulations. Med Biol Eng Comput. 2013;51(11):1209-19.
    • - Ruggieri VG, Anselmi A, Wang Q, Esneault S, Haigron P, Verhoye JP. Computed Tomography Image Processing to Detect the Real Mechanism of Bioprosthesis Failure: Implication for Valve-in-Valve Implantation. J Heart Valve Dis. 2013;22(2):236-8.
    • - Tobon-Gomez C., Geers A. J., Peters J., Weese J., Pinto K., Karim R., Ammar M., Daoudi A., Margeta J., Sandoval Z., Stender B., Zheng Y., Zualaga M., Betancur J., Ayache N., Chikh M. A., Dillenseger J.-L., Kelm, M., Mahmoudi S., Ourselin S., Schaeffer T., Schlaefer A., Ravazi R., Rhode K. S. Benchmark for left atrial segmentation algorithms for 3D CT and MRI dataset. IEEE transactions on medical imaging. 2015. 34(7):1460-1473.

       

      Segmentation of pelvic structures:

       

      Analysis of planning CT images has been investigated in the context of the segmentation of pelvic structures using geometrical shape model tuned by a multi-scale edge detector.

       
        • - Martinez F, Romero E, Drean G, Simon A, Haigron P, de Crevoisier R, Acosta O. Segmentation of Pelvic Structures for Planning Ct Using a Geometrical Shape Model Tuned by a Multi-Scale Edge Detector. Physics in Medicine and Biology. 2014;59(6):1471-84.

           

          New spectroscopy technics to assess renal tumours at surgery:

           

          Wavelet decomposition combined with support vector machine (SVM) was applied to analyze Raman optical spectra. Results have shown that optical spectroscopy techniques can accurately distinguish benign and malignant renal tumours.

           

          Some recent publications:

          • - Fleureau J, Bensalah K, Rolland D, Lavastre O, Rioux-Leclercq N, Guille F, Patard JJ, de Crevoisier R, Senhadji L. Characterization of Renal Tumours Based on Raman Spectra Classification. Expert Systems with Applications. 2011;38(11):14301-6.
          • - Bensalah K, Fleureau J, Rolland D, Lavastre O, Rioux-Leclercq N, Guille F, Patard JJ, Senhadji L, de Crevoisier R. Raman Spectroscopy: A Novel Experimental Approach to Evaluating Renal Tumours. European Urology. 2010;58(4):602-8.
          • - Couapel JP, Senhadji L, Rioux-Leclercq N, Verhoest G, Lavastre O, de Crevoisier R, Bensalah K. Optical Spectroscopy Techniques Can Accurately Distinguish Benign and Malignant Renal Tumours. Bju International. 2013;111(6):865-71.

           

          Fusion and exploitation of multimodal data

           

          Registration and fusion of cardiac images:

           

          The fusion and interpretation of multi-modal information relating anatomical and pathological references in order to establish objective decision-making criteria has been adressed in the contexts of the characterization of myocardial hypertrophy and of the optimization of cardiac resynchronization therapy (CRT).

           
          Registration and fusion of multi-modal data for Cardiac Resynchronisation Therapy (CRT)

          Some recent publications:
          • - Betancur, J., Schnell, F., Simon, A., Tavard, F., Donal, E., Hernández, A. and Garreau, M. Spatio-temporal Registration of 2D US and 3D MR Images for the Characterization of Hypertrophic Cardiomyopathy. In Functional Imaging and Modeling of the Heart. 2013:292-299.
          • - Betancur, J., Simon, A., Langella, B., Leclercq, C., Hernandez, A., Garreau, M. Synchronization and Registration of cine Magnetic Resonance and dynamic Computed Tomography Images of the Heart. IEEE Journal of Biomedical and Health Informatics. 2015: forthcoming.
          • - Tavard, F., Simon, A., Leclercq, C., Donal, E., Hernandez, A.I. and Garreau, M., Multimodal Registration and Data Fusion for Cardiac Resynchronization Therapy Optimization. IEEE Transactions on Medical Imaging 33(6):p.1363-1372, 2014.

             

            Transrectal ultrasound and T2 MRI images fusion in prostate cancer:

             

             

            In the context of focal therapy of prostate cancer, our work dealt with the issue of transrectal ultrasound and T2 MRI images fusion. Methods based on discrete dynamic contours and optimal surface detection, or their combination, have been proposed to delineate the target with minimal user interaction.

             

            Some recent publications:

            • - Garnier C, Bellanger JJ, Wu K, Shu H, Costet N, Mathieu R, de Crevoisier R, Coatrieux JL. Prostate Segmentation in Hifu Therapy. IEEE Transactions on Medical Imaging. 2011;30(3):792-803.
            • - Wu K, Shu HZ, Dillenseger JL. Region and boundary feature estimation on ultrasound images using moment invariants. Computers Methods and Programs in Biomedicine. 2014;113(2):446-455.